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N E W Y O R K C I T Y COLLEGE OF TECHNOLOGY OF THE CITY UNIVERSITY OF NEW YORK 300 JAY STREET • BROOKLYN NEW YORK 11201-2983 Biological Sciences Department Room P-305, Tel: (718) 260-5088

PROPOSAL TO ESTABLISH A

BACHELOR OF SCIENCE PROGRAM IN

BIOMEDICAL INFORMATICS

APPROVED BY THE COLLEGE COUNCIL OF NEW YORK CITY COLLEGE OF TECHNOLOGY

ON FEBRUARY 14, 2012

CONTACT PERSONS Provost Bonne August, Ph.D. Provost, New York City College of Technology [email protected]

Dean Karl Botchway, Ph.D. Interim Dean, School of Arts & Sciences [email protected]

Provost’s Signature: Bonne August, Ph.D.

_________________________________

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mailto:[email protected]

mailto:[email protected]

TABLE OF CONTENTS

TOPIC PAGE Program Identification (Cover Page) 1 1. Introduction 3 2. Purpose and Goals 3 3. Need and Justification

3.1 Relationship to Other Programs at CUNY 3.2 Resources Available to Implement the Program

4 6 6

4. Student Interest and Anticipated Enrollment 6 5. Curriculum

5.1 Overview of Courses in the Proposed Curriculum 5.2 Anticipated Learning Outcomes of the Curriculum 5.3 Courses Required to Complete the Program 5.4 Typical Course Sequences for a 4-Year Timeframe 5.5 Catalog Course Descriptions for Six New Courses for the Program

7 8 8 9

11 14

6. Faculty 15 7. Cost Assessment 15 8. Acknowledgements 15 9. References 15

APPENDICES APPENDIX A Course Syllabi for New Courses

• MED 2400: Medical Informatics Fundamentals • BIO 3352: Bioinformatics II • BIO 3620: Molecular and Cell Biology • BIO 3354: Computational Genomics • BIO 3356: Molecular Modeling in Biology • MED 3910: Internship/Research in Biomedical Informatics

16-44 17 22 28 33 37 41

APPENDIX B Course Descriptions for Existing Upper Level Courses for the Program 45-48 APPENDIX C Program Scheduling 49-50 APPENDIX D Full-Time Faculty Teaching Assignments 51-54 APPENDIX E New Resources 55-56 APPENDIX F Projected Revenue 57-58 APPENDIX G Supporting Materials for Projected Revenue 59-64 APPENDIX H Five Year Financial Projection 65-68 APPENDIX I Articulation Agreement with Borough of Manhattan Community College 69-74 APPENDIX J Letter of Support from Dean Karl Botchway 75-76 APPENDIX K External Letters of Support

• Biomedical Informatics, Columbia University Medical Center • Center for Health Informatics and Bioinformatics, New York Univ. • Biomedical Informatics, University of Utah School of Medicine • American Medical Informatics Association (AMIA) • New York City Economic Development Corporation (NYCEDC)

77-84

APPENDIX L Employment Listings for BS Graduates in Biomedical Informatics 85-96

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1. Introduction

The Biological Sciences Department at New York City College of Technology (City Tech) proposes a Bachelor of Science degree program in Biomedical Informatics. The Biomedical Informatics program will significantly increase opportunities for City Tech students interested in the healthcare and biomedical fields. The outlook is promising for enrollment in such a program. Graduates of the program will be positioned to take advantage of excellent opportunities for employment in the public and private sectors as well as for post-baccalaureate study. The program will also meet a regional need as part of the city’s long-running campaign to become a capital for the biotechnology industry.1

2. Purpose and Goals

The proposed program in Biomedical Informatics will prepare students for enriching careers in the growing field of Biomedical Informatics. The program will equip students with the technical skills and knowledge needed to navigate the mass of biological and biomedical data that is increasingly driving new developments in pharmacology and therapeutics, molecular biology, biomedical science, and healthcare. Upon completing this program, students will have a wide range of career options, from direct employment to continuation of studies in graduate school. In addition, with the proper selection of electives, the program can serve as a springboard to medical school. The program will be truly interdisciplinary, in that technology is used to connect expertise in computer science, medicine, biology, statistics, and healthcare.

A rigorous core of courses will provide students with a strong foundation from which to develop competencies in two interrelated component areas of Biomedical Informatics that form the focus of the program: Molecular Bioinformatics and Health Informatics. This dual focus gives students a broad understanding of the critical importance of informatics for a wide range of biomedical and health applications. While each subfield involves different proficiencies, they share fundamental informatics principles, directed at the transformation of large raw databases into useful biological and biomedical knowledge. Moreover, these two subfields are seeing an exciting integration in cutting edge medicine, as genomic information is used increasingly in medical diagnosis and care. The dual focus of the program thus prepares students for a range of career options and to adapt to changing conditions in the field.

The proposed curriculum also includes courses in general education, advanced biology, and computer systems. These courses provide not only a solid liberal arts education, but also a strong background in biological sciences and computer technology. In addition, they serve as prerequisites for interdisciplinary training in Biomedical Informatics and will prepare students to become creative thinkers able to meet emerging challenges in their studies and careers.

The Molecular Bioinformatics component of the curriculum will train students for careers in industry and academia that require skills for the effective manipulation and analysis of DNA, RNA and protein databases. Concerted efforts in the sequencing of complete genomes of organisms, including the Human Genome Project, have generated vast amounts of raw molecular data. Likewise, proteomic data is becoming increasingly vital in the development of molecular therapies in biotechnology and medicine. For such data to be useful for biomedical and pharmacological applications, extensive biological and computational analyses are required. As expected, we are witnessing an increasing demand for biotechnologists equipped with knowledge of biomedical databases and bioinformatic computer tools, as well as with skills in biostatistics and data mining. The Molecular Bioinformatics courses will prepare graduates of the Biomedical Informatics program for employment as bioinformatics specialists in pharmaceutical and biotech companies, research hospitals, academic institutions, and government-sponsored research institutes. Alternatively, students will be well positioned to enter numerous master’s and doctoral programs in Molecular Bioinformatics at research universities in the region and across the country.

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The Health Informatics component of the curriculum will prepare students for careers with responsibility for the secure storage, retrieval, and use of biomedical information. The Health Insurance Portability and Accountability Acts (HIPAA) of 1996 and 2004 (for small health plans) require national standards for electronic health care records to facilitate electronic processing of claims and other transactions. These laws also require privacy and security standards in order to protect health information. Hospitals and health care centers are eager to maintain an information system that is secure, efficient, timely, patient-centered, equitable, effective and compliant with HIPAA. Experts in the field report a growing demand for trained individuals to assume this responsibility. In addition, President Barack Obama has proposed a massive mobilization to modernize healthcare by making all health records standardized and electronic. The goal is to computerize all health records within five years.2 While it is anticipated that this will result in improved quality of healthcare for all Americans, this initiative also requires skilled health informaticians for its successful implementation. The Health Informatics component of the program will therefore position graduates to seek employment as consultants, hospital record managers, data analysts in industry, librarians, and staff in state health departments and family medical centers.

The program is designed to provide well-rounded, interdisciplinary training for a new generation of biomedical and healthcare workers prepared to meet the challenges of today and of the future. Student knowledge acquired in the college classroom and laboratory will be reinforced by College-sponsored internships (for credit) at clinical and research locations in the region. Because Biomedical Informatics is a rapidly evolving field, it is also important that students benefit from City Tech’s strong General Education requirements and courses, so that they will be able to adapt to changes in this field as creative thinkers and lifelong learners. The goal is not only to provide students with the training they need to enter this growing field in its current state, but also with the personal and intellectual resources to participate in and lead its inevitable advances and transformations.

3. Need and Justification

City Tech’s proposed Biomedical Informatics program addresses employment needs in both Health Informatics and Molecular Bioinformatics, two growing subfields of Biomedical Informatics. Fundamentally, these two areas share a common core of computational and informatics principles, differing only in the kinds of databases that require professional management and scientific analysis.

The manner in which data is managed in the healthcare industry is being transformed. Medical Records and Health Information technicians are being supplemented or replaced by Health Informaticians. The need to strengthen the breadth and depth of the health informatics workforce is a critical component in this transformation. City Tech’s program will ensure the education and training of a new generation of medical and health informaticians that will develop new ways to organize, manage, store, and use information to the benefit of the healthcare industry. They will find the means to communicate this information effectively among the professionals who need it and control the amount and type of information that is disseminated. The Bureau of Labor Statistics3 reports that job opportunities in the field are expected to grow faster than average. Employment is expected to grow 20 percent between 2008 and 2018. Graduates of the program will be fully prepared to assume the responsibilities of a Health Informatician.

Another career path for program graduates will be in Molecular Bioinformatics, as informatics specialists involved in managing and analyzing large biological databases arising from genomic and proteomic research. City Tech’s program will aim to provide students with a solid bioinformatics foundation for careers in pharmaceutical and biotechnology companies. According to the US Department of Labor,4 the projected growth in employment in this young field is higher than average, at 14 to 19 percent between 2008 and 2018.

The need for educational opportunities in Biomedical Informatics is particularly acute in the New York City region. Dr. Constantin F. Aliferis, Director of the Center for Health Informatics and Bioinformatics at New York

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University (NYU), makes this observation in his letter of support for the program (attached in Appendix K). Dr. Aliferis notes that “The New York City area in particular exhibits, in my assessment, a noteworthy discrepancy between on one hand the extraordinary range of resources and activity in Biomedical research and higher education and, on the other hand, the relative insufficiency of BMI research and educational offerings.” He adds that, “Establishing high quality undergraduate training programs such as the one you propose, will help elevate the field by creating better informaticians and do so earlier in their career. This in turn will have catalytic effects in the industry and academia across a wide range of healthcare delivery, biology, biotechnology, and drug development efforts.”

A sampling of employment listings for which bachelor degree graduates in Biomedical Informatics can qualify can be found in Appendix L. These listings for entry-level positions, culled from job search engines and other websites in February 2012, represent the wide range of employment opportunities for graduates of the program. Possibilities include positions in hospitals as bioinformaticians, clinical data specialists, research technicians, and systems analysts; in research institutes as computational biologists and informatics specialists; and in biotech companies as clinical software associates and health record analysts.

Alternatively, graduates will be able to continue study at the graduate level, which should lead to specialist jobs or research positions in both industry and academia. Graduate programs in computational biology and bioinformatics in the tri-state region are looking for qualified applicants, and City Tech is in a good position to establish mutually beneficial relationships with them. The Chair of the Department of Biomedical Informatics at Columbia University Medical Center, which is among the first in the nation to host MA and PhD programs in the field, has provided a letter of support for this proposal. In the letter (attached in Appendix K), Dr. George Hripscak praises the “well-crafted curriculum [which] accurately reflects the core of the field of Biomedical Informatics,” saying that “the fundamental framework of the curriculum as set forth in this program proposal is consistent with the current thinking in the field.” Dr. Hripscak notes that “should your graduates decide to pursue advanced training in the field, they should be well-qualified to apply for admission into masters programs such as ours at Columbia.”

Other related graduate programs exist in the tri-state region. Hunter College has a Bioinformatics MA program; the Polytechnic Institute of NYU has a Bioinformatics MS program; NYU’s Center for Health Informatics and Bioinformatics has recently launched a graduate program in Biomedical Informatics; and SUNY Downstate Medical Center has a Medical Informatics masters program. Some students may proceed to medical schools as well, since the proposed curriculum provides an opportunity to complete many of the courses required to apply to medical school.

The proposed program is among the few in the country to combine courses in health informatics and molecular bioinformatics within an integrated undergraduate curriculum. The letter of support from Dr. Joyce A. Mitchell, Chair of the Department of Biomedical Informatics and Associate Vice President for Academic Health IT at University of Utah School of Medicine, makes this point. Dr. Mitchell says that students who apply to their highly regarded graduate program “come from diverse fields (from biological sciences to computer science), such that in order to gain the necessary multidisciplinary training for Biomedical Informatics, they enter graduate school needing to acquire knowledge and skills that may have not been sufficiently addressed in their undergraduate education. In contrast, graduates of your baccalaureate program will benefit from a comprehensive curriculum that provides training in all aspects of Biomedical Informatics.” Like Dr. Hripcsak, Dr. Mitchell affirms the eligibility of graduates of this program for advanced degree programs. “I do not hesitate to say that we shall be pleased to admit your BS graduates into our graduate programs,” she writes.

The staggering growth in the amount of biological data being generated, including the sequencing of “personal genomes” which are becoming increasingly affordable,5 has created a need for professionals who are adept at engaging such databases for diagnostic and therapeutic purposes. Graduates of the program are poised to be practitioners of the emerging trend called “translational bioinformatics,” whose purpose is to develop and

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implement medical applications based on a meaningful integration of clinical, genomic, and molecular data. Because of the multidisciplinary nature of the proposed curriculum, those graduates seeking to be at the forefront of this exciting field will find a seamless path to any advanced degree towards which they aspire.

3.1. Relationship to Other Programs at CUNY

No other CUNY campus presently offers a BS in Biomedical Informatics. Borough of Manhattan Community College (BMCC) offers an AAS in Health Information Technology, with which the program has formed an articulation agreement (see Appendix I). Graduates of a number of existing associates programs elsewhere may also be interested in pursuing higher education in the proposed program. Programs for which articulation agreements are currently being developed include the AS in Biotechnology at Kingsborough Community College (KCC), AS in Health Sciences at Queensborough Community College (QCC), and AS in Computer Science at Bronx Community College (BCC). The School of Professional Studies (SPS) offers an online BS in Health Information Management, which provides training in health informatics but not in molecular bioinformatics.

3.2. Resources Available to Implement the Program

City Tech presently offers both associate and bachelor’s degrees in numerous health professions: Nursing (AAS and BS), Dental Hygiene (AAS), Health Services Administration (BS), Radiological Technology and Medical Imaging (AAS), Restorative Dentistry (AAS), and Vision Care Technology (AAS). In addition, technology degrees are offered in Computer Science (AS), Microcomputer Business Systems (AAS), Computer Information Systems (AAS), and Computer Systems (BTech). These programs are complemented by a full range of general education courses, some specifically tailored to the needs of health and technology students. Thus, most of the required courses in the proposed Biomedical Informatics program already exist, as well as the needed scientific and computer laboratory facilities.

As a result, only six new courses need to be designed. Importantly, the College currently has faculty with the expertise necessary to develop and teach these new courses. The Biological Sciences Department has been working with the chair and faculty of the Computer Systems Technology Department to develop those courses involving computer technology. Additionally, many of City Tech’s programs in the health profession have faculty members who are familiar with the skill sets needed by health informaticians and should be available for consultation.

Most upper-level courses in the proposed program will be held in computer laboratories, with some held in traditional lecture rooms and biology labs. A number of courses will be offered using partially online or fully online formats. New software will be installed in existing computer laboratories, limiting the cost of this part of the program initially to the cost of the software. The cost of facilities for future expansion has been secured, as the college is moving forward on construction of a new building.

4. Student Interest and Anticipated Enrollment

A large pool of students at City Tech aspires to careers in healthcare professions and the biological sciences. With the creation of the Biomedical Informatics program, these students will have another alternative to the College’s highly competitive health programs, which have limited capacity. Additionally, students who have completed an AS degree in Liberal Arts and Sciences (LAS) can transfer into the program seamlessly and continue towards the bachelor’s degree. Currently, over 1500 students are enrolled in the Liberal Arts programs (LAS and LAA). Finally, graduates of the AS program in Computer Science can continue on to study Biomedical

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Informatics without difficulty, since all their coursework is fully transferrable into the program. The college has offered an elective course in bioinformatics for several semesters which is consistently fully enrolled.

A survey of senior high school students was conducted at a recent City Tech Open House. Of the 104 students who responded, 64 expressed interest in Medical Technology and/or Medical Informatics, and 75 expected to attend college on a full-time basis. A survey of undergraduate students in 23 lecture and lab sections of General Biology I (BIO 1101) was conducted early in the spring of 2009. Of the 693 students surveyed, 122 students indicated that they would be interested in a program in Medical Informatics if it were offered by the College. The survey questions and results are summarized in the table below.

SURVEY QUESTIONS RESULTS For High School Students: How interested are you in enrolling in the Biological Sciences Department’s new programs in Medical Informatics and Medical Technology? (n=104)

very/somewhat interested:

61.5%

not interested: 38.5%

For BIO 1101 Students: Would you be interested in enrolling in the Biological Sciences Department’s new programs in Medical Informatics and Medical Technology? (n=693)

yes 17.6%

no 82.4%

The following table shows a projection of the number of students expected to enroll in the program. We extrapolated from survey results that a moderate number of students who expressed interest will ultimately enroll in the program. The projections shown here assume (a) that two-thirds of the students will enroll on a full-time basis, (b) a steady growth of new full-time and part-time students through the first five years of the program, and (c) a conservative 70% year-to-year retention rate.

Biomedical Informatics Projected Student Enrollment

YEAR I YEAR II YEAR III YEAR IV YEAR V New Cont. New Cont. New Cont. New Cont. New Cont.

Full-time 25 0 30 18 35 34 40 48 45 55 Part-time 15 0 20 11 25 22 30 33 35 44 Sub-totals 40 0 50 29 60 56 70 81 80 99

Totals 40 79 116 151 179

5. Curriculum

City Tech is proposing a bachelor’s degree program in Biomedical Informatics to meet the human resource needs of the growing health and biomedical fields. Biomedical Informatics is the discipline formed by the intersection of computing, healthcare, and biological science. It incorporates the advances arising from the computing revolution and the exponential growth of biomedical data. City Tech’s proposed Biomedical Informatics program is an interdisciplinary major, designed to educate individuals to process seemingly disparate information and integrate into useful knowledge. In addition, the program will produce specialists with practical skills required in the acquisition, maintenance, security, and analysis of health and biomolecular data. Academic experts agree (see Appendix K) that the program’s integrated curriculum is consistent with the current thinking in the field of Biomedical Informatics.

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5.1 Overview of Courses in the Proposed Curriculum

Students will acquire the required competencies through a curriculum designed to include:

1. A strong foundation in the biological sciences, including Anatomy and Physiology and Pathophysiology, combined with the opportunity to take fundamental mathematics and science courses such as calculus, general chemistry, organic chemistry, and calculus-based physics, for those interested in pursuing admission to medical or other professional graduate schools.

2. Significant requirements in computer systems including Programming Fundamentals, JAVA or C++ Programming, Healthcare Databases and Information Systems, as well as in mathematics, including Probability & Statistics.

3. Specially-designed courses in Health Informatics combined with existing courses in Health Services Administration, in order to provide the required background in medicine, medical terminology, healthcare data management, and healthcare organizations. These competencies will link with the student’s skills and knowledge in mathematics, science, and general education to produce competent Health Informaticians.

4. Specially-designed courses in Molecular Bioinformatics, including two semesters of Bioinformatics and one each of Computational Genomics and Molecular Modeling. These courses provide the foundation for competencies in understanding and analyzing genetic, genomic, and proteomic data for cutting-edge healthcare applications and biomedical research.

5. General education core requirements which can be satisfied with existing courses designed for students in the college’s health career programs, and which will enrich the educational experience of Biomedical Informatics students. These include: “The Literature of Illness and Care” (ENG 3404), “Health Care Ethics” (PHIL 2203), and “Specialized Communication for Technology Students” (ENG 1133).

It should be noted that the Biomedical Informatics curriculum is also designed to accommodate students interested in pursuing an MD degree in medical school, with properly chosen elective courses to fulfill pre-med requirements. In particular, such students will be advised by the department curriculum advisor to take general (inorganic) chemistry, organic chemistry, and physics, in addition to the required courses in the program. Most of these additional courses can be accommodated by the program’s curriculum as electives.

5.2. Anticipated Learning Outcomes of the Curriculum

The proposed program is consistent with the mission of the College to provide students “with both a command of skills necessary in their respective career areas, and the educational foundation for lifelong learning.” General Education courses, central to this effort, include a year of English composition, and courses in speech, behavioral and social science, literature and ethics. These courses should provide students with a strong foundation in oral and written communication skills and a well-rounded understanding of human nature and culture.

The program curriculum is designed to meet the following learning goals:

1. A broad general education which lays the ground work for lifelong learning, and prepares for future education at the graduate level.

2. Ability to communicate effectively with other members of the healthcare and information technology professions and research fields.

3. Competencies in general biological sciences and in the fundamentals of computer technology and computer programming.

4. In-depth knowledge of and skills in: a. Computational and mathematical basis of molecular biology and molecular bioinformatics;

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b. Large databases of biomolecular sequence, structure, expression, and interactions, as well as the use of standard bioinformatics software for the retrieval and analysis of information from such databases for biomedical applications;

c. Healthcare information systems analysis and design, including healthcare database structures, data security, privacy, confidentiality, and associated legal and ethical issues.

d. The growing application of molecular bioinformatics in cutting edge medical diagnosis and treatment.

5.3. Courses Required to Complete the Program

The proposed curriculum of the Biomedical Informatics Program, which meets the College’s general education core requirement, is outlined below.

I. General Education Courses (42/43 credits)

General Biology I, BIO 1101/1101L (SCI Core) 4 General Biology II, BIO 1201/1201L (SCI Core) 4 English Composition I, ENG 1101 (ENG Core) 3 The Literature of Illness and Care, ENG 3404 (LIT Core) 3 Health Care Ethics, PHIL 2203 (PHIL Core) 3

Literature/Aesthetics Core Course (LAP Core) 3 Introduction to Psychology, PSY 1101 (BS Core) 3

Behavioral Science Core Course (BS Core) 3 Social Science Core Course (SS Core) 3

Specialized Communications for Technology Students, ENG 1133 (COMM Core) 3 Speech Communication Elective (COMM Core) 3 Calculus I, MAT 1475 4

Probability and Math. Statistics I, MAT 2572 or Statistics with Probability, MAT 1372 3/4

II. Biomedical and Molecular Bioinformatics Courses (29 credits)

Anatomy and Physiology I, BIO 2311/2311L 4 Anatomy and Physiology II, BIO 2312/2312L 4 Pathophysiology, BIO 3526 3 Molecular and Cell Biology, BIO 3620 4 Bioinformatics I, BIO 3350/3350L 4

Bioinformatics II, BIO 3352/3352L 4 Computational Genomics, BIO 3354 3 Molecular Modeling in Biology, BIO 3356 3

III. Computer and Healthcare Informatics Courses (21 credits)

Problem Solving with Computer Programming, CST 1101 3 Programming Fundamentals, CST 1201

or Introductory C++ Programming Language, CST 2403 3 Database Systems Fundamentals, CST 1204 3 Medical Informatics Fundamentals, MED 2400 3 Health Services Management I, HSA 3510 3 Healthcare Databases, MED 4229 3 Healthcare Information Systems, HSA 4620 3

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IV. Internship/Research Course (5 credits)

Internship/Research in Biomedical Informatics, MED 3910 5

V. Major Electives (22/23 credits)

Choose from the following courses listed below. Students must have at least 15 credits in one of the two Elective Areas. The choice of electives, to be made in close consultation with the Program Coordinator or Academic Advisor, should ideally reflect the student’s interests, post-baccalaureate study plans, and career goals.

1. Science and Health Professions Elective Area

Biochemistry, BIO 3601 – 4 credits Physics 1.3, PHYS 1441 – 5 Nutrition, BIO 3524 – 2 Physics 2.3, PHYS 1442 – 5 General Chemistry I, CHEM 1110 – 4 Health Services Management II, HSA 3510 – 3 General Chemistry II, CHEM 1210 – 4 Legal Aspects of Health Care, HSA 3560 – 3 Organic Chemistry I, CHEM 2223 – 5 Health Care Finance and Accounting Management, Organic Chemistry II, CHEM 2323 – 5 HSA 3630 – 3

2. Computation and Computer Systems Elective Area

Operating Systems Fundamentals, CST 1215 – 3 Microcomputer Systems, MST 1205 – 3 Networking Fundamentals, CST 2307 – 3 Local Area Networks, MST 2307 – 4 Web Programming I, CST 2309 – 3 Microcomputer Operating Systems, MST 2405 – 4 Introduction to Systems Analysis and Design – 3 Calculus II, MAT 1575 – 4 Web Programming II, CST 2409 – 3 Discrete Structures and Algorithms I, MAT 2440– 3 C++ Programming Part II, CST 3503 – 3 Discrete Structures and Algorithms II, MAT 2540 – 3 Design of Microcomputer Databases, CST 3504 – 3 Introduction to Linear Algebra, MAT 2580 – 3 Computer Security, CST 3510 – 3 Calculus III, MAT 2675 – 4 Object Oriented Prog. in Java, CST 3513 – 3 Differential Equations, MAT 2680 – 3 Object Oriented Programming, CST 3603 – 3 Probability and Mathematical Statistics II, MAT 3672 – 4 Design of Distributed Databases, CST 3604 – 3 Stochastic Models, MAT 3772 – 3 Database Systems and Programming, MST 1204 – 3 Probability and Mathematical Statistics III, MAT 4872 – 4

Summary of Credits General Education Courses 42/43 Specialized Biology and Molecular Biology Courses 29

Computer and Healthcare Systems Courses 21 Internship/Research 5 Electives 22/23

Total Credits 120

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5.4. Typical Course Sequences for a 4-Year Timeframe

Sample semester-by-semester sequences of courses with three different emphases (Computer Systems, Computation, and Science/Pre-Med) are outlined below. These sequences differ only in the elective courses (indicated in boldface).

Sequence with Emphasis on Computer Systems

First Year Third Year First Semester First Semester BIO 1101/1101L General Biology I 4 BIO 3350/3350L Bioinformatics I 4 ENG 1101 English Composition 3 MED 4229 Healthcare Databases 3 MAT 1475 Calculus I 4 BIO 3620/3620L Molecular and Cell Biology 4 CST 1101 Problem Solving with HSA 3510 Health Services Mgmt. I 3 Computer Programming 3 Total 14

Total 14 Second Semester Second Semester BIO 3352/3352L Bioinformatics II 4 BIO 1201/1201L General Biology II 4 LAP Core Literature/Aesthetics COMM Speech Communication Core Course 3

Elective 3 CST 3504 Design of Microcomputer CST 1201 Programming Fundamentals 3 Databases 3 PSY 1101 Introduction to Psychology 3 BIO 3526 Pathophysiology 3 MAT 1372 Statistics with Probability 3 PHIL 2203 Health Care Ethics 3

Total 16 Total 16

Second Year Fourth Year First Semester First Semester BIO 2311/2311L Anatomy and Physiology I 4 BIO 3354 Computational Genomics 3 CST 1204 Database Systems ENG 3404 The Literature of Illness Fundamentals 3 and Care 3 BS/SS Core Behavioral/Social Science HSA 4620 Healthcare Information Syst. 3 Core Course 3 CST 3604 Design of Distributed MST 1205 Microcomputer Systems 3 Databases 3 ENG 1133 Specialized Communications MST 2405 Microcomputer Operating

for Tech Students 3 Systems 4 Total 16

Total 16 Second Semester Second Semester BIO 3356 Molecular Modeling in Biology 3 BIO 2312/2312L Anatomy and Physiology II 4 MED 3910 Internship/Research in MED 2400 Medical Informatics Biomedical Informatics 5 Fundamentals 3 BS Core Behavioral Science CST 2406 Introduction to Systems Core Course 3

Analysis and Design 3 CST 3510 Computer Security 3 MST 2307 Local Area Networks 4 Total 14

Total 14

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Sequence with Emphasis on Computation

First Year First Semester Third Year BIO 1101/1101L General Biology I 4 First Semester ENG 1101 English Composition 3 BIO 3350/3350L Bioinformatics I 4 MAT 1475 Calculus I 4 MED 4229 Healthcare Databases 3 CST 1101 Problem Solving with MAT 2572 Probability and Mathematical Computer Programming 3 Statistics I 4

Total 14 BIO 3620/3620L Molecular and Cell Biology 4 Second Semester Total 15 BIO 1201/1201L General Biology II 4 Second Semester COMM Speech Communication BIO 3352/3352L Bioinformatics II 4

Elective 3 LAP Core Literature/Aesthetics CST 2403 Introductory C++ Core Course 3 Programming Language 3 HSA 3510 Health Services Mgmt. I 3 PSY 1101 Introduction to Psychology 3 PHIL 2203 Health Care Ethics 3 MAT 1575 Calculus II 4 BIO 3601 Biochemistry 4

Total 17 Total 17

Second Year Fourth Year First Semester First Semester BIO 2311/2311L Anatomy and Physiology I 4 BIO 3354 Computational Genomics 3 CST 1204 Database Syst. Fundamentals 3 ENG 3404 The Literature of Illness BS/SS Core Behavioral/Social Science and Care 3 Core Course 3 MAT 2580 Intro. to Linear Algebra 3 MAT 2440 Discrete Structures and BIO 3526 Pathophysiology 3 Algorithms I 3 BIO 3524 Nutrition 2 ENG 1133 Specialized Communications Total 14

for Tech Students 3 Second Semester Total 16 BIO 3356 Molecular Modeling in Biology 3

Second Semester MED 3910 Internship/Research in BIO 2312/2312L Anatomy and Physiology II 4 Biomedical Informatics 5 CST 3503 C++ Programming II 3 BS Core Behavioral Science MED 2400 Medical Informatics Core Course 3 Fundamentals 3 HSA 4620 Healthcare Information Syst. 3 MAT 2540 Discrete Structures and Total 14 Algorithms II 3

Total 13

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Sequence with Emphasis on Science (for Pre-Med Students)

First Year First Semester First Semester BIO 3350/3350L Bioinformatics I 4 BIO 1101/1101L General Biology I 4 MED 4229 Healthcare Databases 3 ENG 1101 English Composition 3 PHYS 1441 Physics 1.3 5 MAT 1475 Calculus I 4 CST 1204 Database Systems CST 1101 Problem Solving with Fundamentals 3 Computer Programming 3 Total 15

Total 14 Second Semester Second Semester BIO 3352/3352L Bioinformatics II 4 BIO 1201/1201L General Biology II 4 LAP Core Literature/Aesthetics COMM Speech Communication Core Course 3

Elective 3 HSA 3510 Health Services Mgmt. I 3 CST 1201 Programming Fundamentals 3 PHYS 1442 Physics 2.3 5 PSY 1101 Introduction to Psychology 3 Total 15 CHEM 1110 General Chemistry I 4

Total 17 Fourth Year First Semester

Second Year BIO 3354 Computational Genomics 3 First Semester ENG 3404 The Literature of Illness BIO 2311/2311L Anatomy and Physiology I 4 and Care 3 MAT 1372 Statistics with Probability 3 HSA 4620 Healthcare Information Syst. 3 ENG 1133 Specialized Communications PHIL 2203 Health Care Ethics 3

for Tech Students 3 BIO 3526 Pathophysiology 3 CHEM 1210 General Chemistry II 4 Total 15

Total 14 Second Semester Second Semester BIO 3356 Molecular Modeling in Biology 3 BIO 2312/2312L Anatomy and Physiology II 4 MED 3910 Internship/Research in BIO 3620/3620L Molecular and Cell Biology 4 Biomedical Informatics 5 MED 2400 Medical Informatics BS Core Behavioral Science Fundamentals 3 Core Course 3 CHEM 2223 Organic Chemistry I 5 BS/SS Core Behavioral/Social Science

Total 16 Core Course 3 Total 14

Third Year

In summary, the proposed BS program in Biomedical Informatics will provide rigorous and specialized technical training within an interdisciplinary curriculum, designed to be sufficiently flexible to fulfill the growing need for information specialists, researchers, and educators who can perform in various roles requiring healthcare and medical competencies as well as technological and computational proficiency.

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5.5. Catalog Course Descriptions of the Six Courses to be Established for the Program

Molecular and Cell Biology, BIO 3620 3 cl hrs, 3 lab hrs, 4 cr Prerequisite: BIO 1101 and ENG 1101

An overview of eukaryotic cells including the molecular basis for its structure and functions. Topics introduce key principles of Cell Biology, including cellular energetics and biochemistry, roles of cell membranes and the detailed functions of organelles. Molecular structure of DNA, RNA and Proteins will be discussed as well as Transcription, Translation and Post-translational modifications. Cell signaling pathways, cell cycle and cell death will be discussed, with the detailed reference to its regulations. The laboratory component provides in-depth experimentation with the techniques and tools utilized in the study of molecular and cell biology.

Bioinformatics II, BIO 3352 2 cl hrs, 4 lab hrs, 4 cr Prerequisite: BIO 3350

A continuation of Bioinformatics I. Advanced topics in structural bioinformatics, functional genomics, and evolutionary processes. The course covers molecular evolution and phylogenetics; protein structure and stability, protein folding, and computational structure prediction of proteins; proteomics; protein-nucleic acid interactions; RNA bioinformatics, microarray and expression data; and systems biology. The lab component of the course introduces computational tools used to implement analysis of sequence, structural, and functional data.

Computational Genomics, BIO 3354 3 cl hrs, 3 cr Prerequisite: BIO 3352

Covers selected advanced topics in computational genomics. Modern DNA microchips enable measurement of the activity state of tens of thousands of genes in a cell, and related techniques are being developed for measuring the protein contents. In this course students will utilize modern statistical and computational methods to understand biological processes. This course emphasizes studies of gene and cell function made possible by recent advances in measurement technology, statistical and computational methods.

Molecular Modeling in Biology, BIO 3356 3 cl hrs, 3 cr Prerequisite: BIO 3352

This course covers the applications of computer modeling and simulation to problems involving biological macromolecules. The targeted areas are in protein structure modeling, structure-based drug design, drug screening, cheminformatics, and intermolecular interactions and binding. Students will learn the theory and algorithms underlying a variety of simulation techniques.

Medical Informatics Fundamentals, MED 2400 3 cl hrs, 3 cr Prerequisite: BIO 2311

An introduction to the current practice of medical informatics. Major course topics address challenges related to the implementation of electronic health records (EHR) and other medical and healthcare databases in patient care settings, and their effective use in managing and improving personal and public health. Related topics include acquisition, storage, use and representation of medical data; medical terminology and associated databases; health information management and retrieval methods; privacy and security of health data; evidence-based medicine; and a survey of ethical, legal, and political issues at play in the technological shifts in the field of medical informatics.

14

Internship/Research in Biomedical Informatics, MED 3910 225 field hrs total, 5 cr Prerequisites: MED 4229, BIO 3352, and permission of program coordinator.

An internship/research course that exposes majors to the practice of medical informatics and molecular bioinformatics in commercial, research, and medical settings.

6. Faculty

The Biological Sciences Department has 20 tenured or tenure-track faculty, of whom ninety percent hold a Ph.D. degree. More than 50 adjunct faculty members are hired each semester. A reserve pool of adjunct faculty, many with PhDs, is also available. The current faculty are qualified to teach all of the courses that will be hosted by the Department for the proposed program. Three faculty members have expertise in bioinformatics, and are active in bioinformatics and computational biology research. The Health Services Administration Program consists of three faculty members with field experience. The Computer Systems Technology (CST) Department has 19 faculty members, of whom two-thirds hold a PhD degree. Dr. Candido Cabo, professor of CST, specializes in research on computer modeling of biological systems.

7. Cost Assessment

The program will draw substantially on existing curricula, academic structures, and faculty resources within City Tech. Additional computer classrooms may be needed as the program grows, but are not required at the start of the program. While most software programs are freely available in the public domain, some specialty software will have to be acquired. The cost will be provided through normal college channels and available technology funds.

8. Acknowledgements

This proposal has benefited from expert review and feedback from Dr. George Hripscak, Chair of the Department of Biomedical Informatics at Columbia University Medical Center and Director of Medical Informatics Services at New York-Presbyterian Hospital/Columbia (letter of support in Appendix K); Dr. Constantin F. Aliferis, Director of the Center for Health Informatics and Bioinformatics at New York University (letter of support in Appendix K); Dr. Joyce Mitchell, Chair of the Department of Biomedical Informatics and Associate Vice President for Academic Health IT at University of Utah School of Medicine (letter of support in Appendix K); Dr. James Cimino, Chief of the Laboratory of Informatics Development at the National Institutes of Health; and Prof. Lynda Carlson, program director of the Health Information Technology program in Borough of Manhattan Community College (BMCC), who also assisted in formulating the Articulation Agreement (see Appendix I). Letters of support for the proposed program have also been received from the American Medical Informatics Association (AMIA) and New York City Economic Development Corporation (NYCEDC).

9. References

1. http://www.nycbiotech.org/overview.html, accessed 21 February 2012. 2. http://money.cnn.com/2009/01/12/technology/stimulus_health_care/?postversion=2009011204, accessed 21

February 2012. 3. http://www.bls.gov/oco/ocos103.htm, accessed 21 February 2012. 4. http://online.onetcenter.org/link/details/19-1029.01, accessed 21 February 2012. 5. http://www.nature.com/news/2010/100914/full/news.2010.465.html, accessed 21 February 2012.

15

http://www.nycbiotech.org/overview.html�

http://money.cnn.com/2009/01/12/technology/stimulus_health_care/?postversion=2009011204�

http://www.bls.gov/oco/ocos103.htm�

http://online.onetcenter.org/link/details/19-1029.01�

http://www.nature.com/news/2010/100914/full/news.2010.465.html�

http://www.nycbiotech.org/overview.html

APPENDIX A: COURSE SYLLABI FOR NEW COURSES

16

NEW COURSE PROPOSAL

MEDICAL INFORMATICS FUNDAMENTALS

NEW YORK CITY COLLEGE OF TECHNOLOGY The City University Of New York School of Arts and Sciences

Biological Sciences Department

Course Information Course title: Medical Informatics Fundamentals Course code: MED 2400 Credit Hours: 3 credit hours

3 hours lecture per week Prerequisite: BIO 2311 Text: Biomedical Informatics: Computer Applications in Health Care and

Biomedicine, 3rd Edition (2006) by Edward H. Shortliffe (Editor), James J. Cimino (Associate Editor). (A new edition is forthcoming.)

Course Catalog Description:

An introduction to the current practice of medical informatics. Major course topics address challenges related to the implementation of electronic health records (EHR) and other medical and healthcare databases in patient care settings, and their effective use in managing and improving personal and public health. Related topics include acquisition, storage, use and representation of medical data; medical terminology and associated databases; health information management and retrieval methods; privacy and security of health data; evidence-based medicine; and a survey of ethical, legal, and political issues at play in the technological shifts in the field of medical informatics.

Additional Suggested Reading:

Lecture notes, journal articles, and other reading materials provided by the instructor.

Proposer Information Name: Armando D. Solis, Ph.D. Phone: (718) 260-5894 Email: [email protected]

EXTENDED COURSE DESCRIPTION

This course provides a full introduction to the issues involved in the current practice of medical informatics. Major course topics address challenges related to the implementation of electronic health records and other medical and healthcare databases in patient care settings, and their effective use in managing and improving personal and public health. Through timely examples and real-life case studies, students will understand medical informatics as a critical component of the practice of medical care and public health. Topics covered in the semester include acquisition, storage, use and representation of medical data; medical terminology and associated databases; health information management and retrieval methods; privacy and security of health data; electronic

17

health records (EHR); evidence-based medicine; and a survey of ethical, legal, and political issues at play in the technological shifts in the field of medical informatics.

ANTICIPATED LEARNING OBJECTIVES

Upon satisfactory completion of the course, the student will be able to:

1. describe how the healthcare information infrastructure is used to collect, process, maintain, exchange, and disseminate data.

2. demonstrate familiarity with information systems that employ communication and computer technology to collect, maintain, access, evaluate, and interpret healthcare/public health data.

3. demonstrate understanding of the use of informatics methods and resources as strategic tools to improve healthcare delivery and public health.

4. articulate the importance of collaboration among medical, public health, communication, and informatics specialists in the process of design, implementation, and evaluation of healthcare/public health programs.

5. articulate legal and ethical principles fundamental to the use of information technology and resources in healthcare/public health settings.

6. explain issues of privacy, confidentiality, and security of medical data in the context of an electronic information infrastructure.

7. demonstrate effective written and oral skills for communicating with different audiences in the context of professional healthcare/public health activities.

ASSESSMENT OF SPECIFIC LEARNING OUTCOMES

LEARNING OUTCOMES ASSESSMENT Use proper terminology related to information systems used to collect, maintain, and access medical data.

Quizzes and exams that are given throughout the semester.

Articulate the need for standard and controlled terminology in the digitization of clinical and biomedical data.


Describe information systems in current use in medical and public health centers and how they are used in practice.

Multiple-choice and short-answer quizzes; essay-type answer exams.

Discuss the history and development of the Electronic Health Record (EHR), the parts of the EHR, and its current and intended use in healthcare settings.

Short-answer quizzes and essay-type answer exams.

Articulate the need for, as well as issues relating to, EHR in the delivery and quality of healthcare.


Compare health information systems in different clinical settings (i.e., hospital, clinic, laboratory, radiology, and pharmacy), and describe the common and unique features of each.


Discuss the ways in which health information systems contribute to the improvement of public health.


Describe the processes involved in health finance and insurance systems, and discuss the issues involved in health insurance.


Explain how bioinformatics and biomedical informatics Short-answer quizzes and essay-type answer exams.

18

can assist in biomedical research. Identify ways in which data mining of biological and health record databases can improve healthcare.


Describe the impact of health informatics technologies on clinical decision making.


Participate in an informed discussion and debate about the ethical issues relating to the EHR and other public health information technologies.

Short-answer quizzes and essay-type answer exams; evaluation of online Discussion Board forum participation; class participation.

Discuss the legal ramifications of the use of EHR and associated data in healthcare delivery.

Short-answer quizzes and essay-type answer exams; evaluation of Discussion Board forum participation; class participation.

Explain the political issues (both domestic and international) at play in mandating EHR use.

Short-answer quizzes and essay-type answer exams; evaluation of Discussion Board forum participation; class participation.

Identify new and emerging informatic technologies that could transform healthcare in the future.


Design a project report plan and formulate appropriate scientific questions to be addressed in the project.

Evaluation of Research Project Worksheets to track progress of research work.

Efficiently use online and library resources to gather appropriate information sources, and incorporate these in a coherent written report.

Evaluation of Research Project Worksheets to track progress of research work; evaluation of semester-long research project.

Be able to express complex scientific ideas and social issues orally, in a clear and critical manner.

Evaluation of oral report of the class project; instructor evaluation of class participation.

Incorporate many health informatics and bioinformatics topics covered in class into a coherent final project.


TOPICAL LECTURE OUTLINE

WEEK TOPIC

1

PART 1: Themes in Medical Informatics UNIT I: What is Medical Informatics?

• The Goals of Medical Informatics • A Brief History of Medical Informatics • The Organization of Medicine and Healthcare • Systems Design Considerations for the Clinical User

2

UNIT II: Controlled Medical Terminology • A Taxonomy of Medical Informatics • Standards in medical informatics • MeSH (Medical Subject Headings)

3

• UMLS(Universal Medical Language System) • Specific systems including ICD9, SNOMED, LOINC • Adverse Drug Reaction Terminology, RxNORM and OMIM • Case Studies

4 UNIT III: The Electronic Health Record (EHR) • The Organization of Health Information (CCHIT, HL7, HIMSS, DICOM, CCR,

19

XML) • The Paper-based Medical Record • Current Use of EHR in Healthcare Settings • VistA (VA EHR System)

EXAM 1

5

• Issues with EHR • History, Organization • Case Studies • Current Projects and Latest Technologies • Impact on Quality of Care

6

Part II: Medical Informatics and Health Information Systems UNIT IV: Health Information Systems in Clinical Settings

• Hospital Information Systems • Clinic Information Systems • Laboratory Information Systems • Radiology Information Systems • Pharmacy Information Systems

7

UNIT V: Health Information Systems in Public Health • Disease Surveillance (NEDSS) • Chronic Disease Management • Disease Registries • Epidemiology

8

• Health Indicators (BioSense, Health Information Exchange) • Statistical Reporting • International Health (in the Developed and Developing World) • International Health Agencies • Disaster Informatics

EXAM 2

9

UNIT V: Systems for Health Finance and Health Insurance • Methods of Payment • Payer-side systems • Provider-side systems • Managed Care and Managed Costs • Case Studies

10

Part III: Applications of Medical Informatics and Related Issues UNIT VI: Informatics Issues in Virtual Healthcare, Telemedicine, and Expert Systems

• eHealth • Virtual Healthcare Delivery System • Issues in Telemedicine: Real-time, Store-and-forward

11 • Artificial Intelligence in Medicine • Expert Systems in Medicine

12

UNIT VII: Medical Informatics and Clinical Decision Making • Measuring Quality and Outcomes • Standards and Quality Improvement • Evidence-Based Medicine • Case Studies

EXAM 3 13 UNIT VIII: Ethical, Legal, and Political Issues (HIPAA)

20

• Accessibility vs. Confidentiality • Health as a Human Right • Laws Relating to Healthcare • Ethical Use of Medical Data for Public Health Research • Case Studies

14

UNIT IX: Future Technologies • Integrating the Personal Health Record with Mobile Technology • Personalized Medicine • Genome-based Medical Care • Various readings from current literature on future trends

15 Project Presentations FINAL EXAMINATION

GRADING PROCEDURE

Student scores from quizzes (15%), take-home (online) assignments (15%), final class project and presentation (15%) (see details below), class participation (both in-class and online) (5%), and four exams (50%), including one comprehensive final exam, will constitute the final grade.

RESEARCH PROJECT AND CLASS PRESENTATION

The research project, which accounts for 15% of the final grade, involves: (1) a formal write-up of at least 5 pages (not including the cover page), using 1.5 line spacing (not double spaced); and (2) a 8-10 minute oral presentation in class. Class presentations will be held on the last week of the semester, and the written reports will be due on the last class meeting.

A list of suggested topics of current interest in medical informatics will be provided. However, students are encouraged to explore other topics outside the list. Students will discuss their research topic with the instructor by Week 10 of the course. During the succeeding weeks, students will be expected to accomplish 3 Research Project Worksheets, designed to guide them through the many steps of organizing a comprehensive research project and oral presentation.

CLASS PARTICIPATION

Participation is key to making everyone’s experience pleasant and productive. Participation means not only that the student be present in class (or online), but also that the student should:

• review all course sections and complete all weekly assignments on a timely basis; • fully cooperate and collaborate with classmates in group work assignments and exercises. • actively and interactively participate in each lecture’s discussion in the classroom and online. This

requirement applies to students whether they are taking the course online (fully or partially online) or face to face.

21

NEW COURSE PROPOSAL

BIOINFORMATICS II

NEW YORK CITY COLLEGE OF TECHNOLOGY The City University Of New York

School of Arts and Sciences Biological Sciences Department

Course Information Course title: Bioinformatics II (Lecture and Laboratory) Course code: BIO 3352 Credit Hours: 4 credit hours

2 hours LECTURE and 4 LAB hours per week Prerequisite: BIO 3350 Text: Understanding Bioinformatics by Marketa Zvelebil & Jeremy O. Baum, Garland

Science, New York (2008). Course Catalog Description:

A continuation of Bioinformatics I. Advanced topics in structural bioinformatics, functional genomics, and evolutionary processes. The course covers molecular evolution and phylogenetics; protein structure and stability, protein folding, and computational structure prediction of proteins; proteomics; protein-nucleic acid interactions; RNA bioinformatics, microarray and expression data; and systems biology. The lab component of the course introduces computational tools used to implement analysis of sequence, structural, and functional data.

Additional Suggested Reading:

Lecture notes and web resources provided by instructor, and supplementary materials including scientific journal articles and other scholarly literature.



Upon satisfactory completion of the course, the student will:

1. understand fundamental principles behind key molecular biology concepts such as molecular evolution, phylogeny, gene structure, and protein structure and folding.

2. understand the mathematical basis of statistical tools and computational algorithms and their role in processing large databases to discover new biological insight.

3. be proficient in utilizing online resources such as the National Center for Biotechnology Information (NCBI) to locate data relevant to any particular biological question or problem.

4. be able to use commonly used bioinformatics programs available online to analyze DNA sequence data for

22

gene detection; amino acid sequence data for protein structure prediction; and microarray expression data for expression analysis and classification.

5. be aware of the importance of structural and functional analysis in biological and biomedical research. 6. be able to synthesize complex bioinformatics and biological knowledge, and use appropriate bioinformatic

tools to address a particular research question. 7. demonstrate effective written and oral skills in discussing bioinformatics concepts and issues.


LEARNING OUTCOMES ASSESSMENT Explain the molecular basis of evolution, and describe how bioinformatics can uncover phylogenetic relationships.


Use distance measures to construct phylogenetic trees. Evaluation of lab module report and problem solving exercises.

Identify appropriate phylogenetic models for various cases, and recognize the variety of phylogenetic models in use.

Multiple-choice and short-answer quizzes; essay-type answer exams; evaluation of lab module report and problem solving exercises.

Navigate the NCBI website, and locate the database(s) appropriate to the given problem.

Evaluation of lab module report; evaluation of semester-long research project.

Describe the structure and features of both prokaryotic and eukaryotic genomes, and explain how these can be exploited in gene detection and prediction.


Explain the theory behind the algorithms used for intron/exon and splice site prediction.


Use commonly available software for gene detection and prediction, as well as intron/exon and splice site prediction.

Evaluation of lab module report and problem solving exercises.

Recognize the need for gene ontology and genome annotation.


Use accuracy measures to assess prediction algorithms. Evaluation of lab module report and problem solving exercises.

Discuss the methodologies behind commonly used secondary structure prediction algorithms, and use them to analyze protein sequences.


Conduct searches in the Protein Data Bank (PDB) and the NCBI for protein sequences, and visualize molecular structure using visualization programs.


Explain how score functions and potential energy functions are derived from databases, and demonstrate the mechanics using real data.


Discuss the problem of protein folding and protein structure prediction, and explain the importance of these in biological and medical research and understanding.


Conduct tertiary structure prediction using popular web-based computational tools.


Explain the role of statistical tools in bioinformatics research.


Utilize computer programs for protein function Evaluation of lab module report and problem solving

23

prediction. exercises. Discuss the computational basis of large expression data (for both genes and proteins), and use programs to undertake expression analysis with real data.


Discuss fundamental aspects of molecular interaction Multiple-choice and short-answer quizzes; essay-type networks, metabolomics, functional genomics. answer exams. Design a project report plan and formulate appropriate Evaluation of Research Project Worksheets to track scientific questions to be addressed in the project. progress of research work. Efficiently use online and library resources to gather appropriate information sources, and incorporate these in a coherent written report.


Be able to express complex scientific ideas orally, in a clear and critical manner.

Evaluation of oral report of the class project; instructor evaluation of class participation.

Incorporate many bioinformatics topics covered in class into a coherent final project.


TOPICAL LECTURE AND LABORATORY OUTLINE

WEEK TOPICS COVERED

1

LECTURE: Evolutionary Processes I • Molecular Evolution and Evolutionary Models • Evolutionary Distance Calculations and Phylogenetic Trees

LAB 1: Structure and Interpretation of Phylogenetic Trees

2

LECTURE: Evolutionary Processes II • Generating Single Phylogenetic Trees • Generating Multiple Tree Topologies • Evaluation of Tree Topologies and Tree Comparison

LAB 2: Phylogenetic Tree Reconstruction

3

LECTURE: Genomics I • Structure of Prokaryotic and Eukaryotic Genomes • Gene Features for Gene Prediction in Prokaryotes and Eukaryotes

LAB 3: Exploring Whole Genome Databases in NCBI

4

LECTURE: Genomics II • Splice Site and Exon/Intron Structure Prediction • Gene Signals and Features Used in Gene Detection • Markov Chain Methods in Sequence and Genomic Analysis

24

LAB 4: Computational Tools for Prokaryotic Gene Prediction

5

EXAM I

LAB 5: Computer Programs for Eukaryotic Gene Prediction and Splice Site Detection

6

LECTURE: Genomics III • Large Genome Comparisons • Gene Ontology and Genome Annotation • Confirmation of Gene Predictions and Accuracy Measures

LAB 6: Practical Genome Annotation

7

LECTURE: Protein Structure I • Problem of Protein Structure Prediction from Amino Acid Sequence • Secondary Structure and Secondary Structure Prediction Algorithms • Assessing the Accuracy of Prediction Programs

LAB 7: Exploring the Protein Data Bank (PDB) and Molecular Structure Visualization Programs

8

LECTURE: Protein Structure II • Statistical and Knowledge-Based Methods for Structure Prediction • Role of Scoring Functions (Potential Energy Functions) Work in Structure Prediction • Neural Network Methods and Hidden Markov Models in Structure Prediction

LAB 8: Secondary Structure Prediction using PREDATOR and PSIPRED

9

LECTURE: Protein Structure III • Protein Folding (Experimental and Theoretical) • Force Fields • Tertiary Structure Prediction • Principles and Steps in Homology Modeling and Threading

LAB 9: Homology Modeling, MODELLER, and Threading

10

EXAM II

LAB 10: Protein Function Prediction

11 LECTURE: Protein Structure IV

• Protein Function • Functional Conservation, Finding Binding and Active Sites, docking Methods

25

• Quaternary Structure and Protein-Nucleic Acid Interaction

LAB 11: Scientific Literature, PubMed, and Effective Research Practice

12

LECTURE: Systems Biology I • Proteomics • Large-Scale Gene and Protein Expression Analysis

LAB 12: Microarray Data Analysis

13

LECTURE: Systems Biology II • Molecular Interaction Networks, Functional Genomics, and Metabolomics • Cluster Analysis • Network Analysis • Statistical Tools for Classification based on Gene and Protein Expression Data

LAB 13: Cluster Analysis in Expression Data for Classification

14

LECTURE: Special Topics • Advances in the Bioinformatics of the Human Genome and their Applications in

Medicine and Healthcare • Computational Drug Design • Medical Informatics: The Use of Patient Health Records in Biomedical Research

LAB 14: Preparation for Class Presentations and Research Reports

15

EXAM III (FINAL EXAM)

LAB 15: Class Presentations of Research Projects

GRADING PROCEDURE

LECTURE: The lecture grade accounts for 40% of the final grade. Three exams, including one comprehensive final exam, will comprise the lecture grade.

LABORATORY: The laboratory grade accounts for 60% of the final grade. This portion of the final grade is subdivided into the following components: bi-weekly quizzes (15%), weekly lab exercise reports (25%), final research project written report and oral presentation (15%) (see details below), and class participation, both in-class and online (5%).

26

RESEARCH PROJECT AND CLASS PRESENTATION

The research project, which accounts for 15% of the final grade, involves: (1) a formal write-up of at least 5 pages (not including the cover page), using 1.5 line spacing (not double spaced); and (2) a 8-10 minute oral presentation in class. Class presentations will be held on the last day of lab, and the written reports will be due on the lecture meeting time prior to the last lab.

A list of suggested topics of current interest in structural and functional bioinformatics will be provided. However, students are encouraged to explore other topics outside the list. Students will discuss their research topic with the instructor by Week 10 of the course. During the succeeding weeks, students will be expected to accomplish 3 Research Project Worksheets, designed to guide them through the many steps of organizing a comprehensive research project and oral presentation.

CLASS PARTICIPATION

Participation is key to making everyone’s experience pleasant and productive. Participation means not only that the student be present in class (or online), but also that the student should:

• review all course sections and complete all weekly assignments on a timely basis; • fully cooperate and collaborate with classmates in group work assignments and lab exercises. • actively and interactively participate in each lecture’s discussion in the classroom and online. This

requirement applies to students whether they are taking the course online (fully or partially online) or face to face.

27

PROPOSAL FOR NEW COURSE

MOLECULAR AND CELL BIOLOGY


School of Arts and Sciences Department of Biological Sciences

Course Information Course title: Molecular and Cell Biology Course code: BIO 3620 Credit Hours: 4 credit hours

3 lecture class hours/week, 3 laboratory class hours/week Prerequisites: BIO 1101 and ENG 1101 Text: 1. Molecular Biology of the Cell, 4th Edition, by Alberts B. et.al. (Published by Garland

Science, 2002) 2. Laboratory Manual: Laboratory Manual for Cell And Molecular Biology, 6th Edition

(Published by Burgess Publishing Co., 2000) Course Catalog Description:

An overview of eukaryotic cells including the molecular basis for its structure and functions. Topics introduce key principles of Cell Biology, including cellular energetics and biochemistry, roles of cell membranes and the detailed functions of organelles. Molecular structure of DNA, RNA and Proteins will be discussed as well as Transcription, Translation and Post-translational modifications. Cell signaling pathways, cell cycle and cell death will be discussed, with the detailed reference to its regulations. The laboratory component provides in-depth experimentation with the techniques and tools utilized in the study of molecular and cell biology.

Additional Reading: Lecture handouts will be provided

Proposer Information Name: Dr. Sanjoy Chakraborty and Dr. Laina Karthikeyan Phone: (718)-260-5968; (718)-260-5953 Email: [email protected]; [email protected]

LEARNING OBJECTIVES

• To understand the structure and function of eukaryotic cells. • To understand the key principles of cellular metabolism, cell-cell recognition, role of membranes and cell

signaling pathways. • To develop a detailed understanding of the central dogma of biology, “DNA to RNA to Protein”

mechanisms at the molecular level. • To understand the cell cycle and programmed cell death, and its regulations. • To understand the molecular biology of cancer and its future.

28

mailto:[email protected]�



LEARNING OUTCOMES ASSESSMENT Understand how to succeed in this course Complete pre-course quiz on the first day of the class. Understand the reading materials: information from text book or research paper

Group discussion of research paper; short answer quizzes, and exam questions.

Critically evaluate the biological process and be able to interpret the results.

Short answer quizzes, assignments, and exam questions

Understanding the molecular mechanism of the signalling pathway of the cell

Short answer quizzes and exams. Evaluation of project and a short research paper

Critical understanding of molecular structure of DNA, RNA and Proteins

Short answer quizzes, assignments and exams.

Identify the molecular processes namely, replication, transcription, translation.

Short answer quizzes, assignments and exams.

Discuss scientific materials and any ideas in a logical and accurate manner

Observation of instructor. Participation in group-discussion in the class.

Survey recent reports through extensive literature search in order to collect materials for research paper (library or internet-based analysis).

Observation of instructor. Evaluation of the assignments and paper using rubric.

Design and write a research paper using appropriate references, experimental data, correct scientific language, spelling and grammar; written in a formal scientific journal format.

Evaluation of assignments and semester long research paper based on the provided rubric.


Week Lecture

1

Introduction to eukaryotic cells and genetic information in eukaryotes: • Cytoskeleton: Self-assembly and dynamic structure of cytoskeletal filaments • Regulation of cytoskeletal filaments • Molecular motors

2 Cell Chemistry:

• The chemical components of cells; • Catalysis and the use of energy by the cell

3

The shape and structure of Proteins: • Folding patterns: Alpha helix and beta sheet • Sequence homology search: Identify close relatives • Multiple subunits; self-assembly

4

The functions of Proteins: • Protein conformation • Binding sites • Enzymes: catalysis; substrate binding • The catalytic activities of enzymes are regulated • Allosteric enzyme

5 Exam – 1 Structure of cell membrane:

29

• Fluidity of Lipid bilayer; Lipid rafts enriched in Sphingolipids, Cholesterol, and some membrane proteins

• Transmembrane protein channels: Alpha helical conformation and Beta barrels

6 Membrane structure and transport: • Principles of membrane transport • Carrier proteins; ion channels and electrical properties of membranes

7

Intracellular compartments and protein sorting: • The compartmentalization of the cell • The transport of molecules between the nucleus and the cytosol • The transport of protein into mitochondria • Endoplasmic reticulum: Signal Recognition Particle (SRP)

8

Intacellular vesicular traffic- the molecular mechanisms: • Molecular mechanisms of membrane transport and the maintenance of

compartmental diversity: Coated vesicles, SNARE proteins and targeting GTPases • Vesicle Docking: Rab proteins • Transport from ER to Golgi apparatus • Transport from Trans Golgi to Lysosomes

9

Exam – 2 Energy conversion- mitochondria:

• Electron transport chains and their proton pumps • Electrochemical proton gradient across the inner membrane • Chemiosmotic process: Oxidation energy into ATP • The genetic systems of Mitochondria

10

DNA and chromosomes: • Replication, repair and recombination • DNA structure; Chromosomal DNA and its packaging • DNA Replication mechanism: RNA primer, replication origins, direction, replication

fork, proofreading • DNA repair • General Recombination and Site specific Recombination

11

How cells read the genome - DNA to Protein: • DNA to RNA: RNA polymerase and other transcription factors • RNA capping, RNA splicing • RNA to Protein • Genetic switches and posttranslational controls

12

Exam – 3 Cell communication:

• Signaling through G-protein • Signaling through enzyme linked cell surface receptors • Signaling pathways that depend on regulated proteolysis

13

The cell cycle and programmed cell death: • Overview of the cell cycle • Components of cell cycle control system • Intracellular control of cell cycle events • Programmed cell death: Apoptosis • Extracellular control of cell division, cell growth, and Apoptosis

14 Cancer: molecular basis of cancer: • Finding the cancer-critical genes

30

• The preventable causes of cancer • Treatment: present and future

15 Exam 4 (Final Exam)

Participation: Classroom participation is not only the key for success but it also creates a pleasant and friendly environment, which support enhanced learning. However, participation does not merely indicate the presence of a student in the classroom, but it is the active involvement. Students should:

• Prior to attending any classes review all course materials and complete all assignments and any homework given by the instructor on a timely basis.

• Ask thought-provoking questions about the topics and evaluate the topic presentations. Get involved in any group-discussions actively in the classroom and/or online. This is a requirement, and applies to students whether they are taking the course online or face-to-face.

MOLECULAR AND CELL BIOLOGY LABORATORY

Molecular and Cell Biology Laboratory (3 laboratory hours) Current techniques that are utilized in a modern Molecular and Cell Biology research laboratory. Practical skills taught include fundamental microscopy, monitoring bacterial growth, plasmid isolation, restriction digest analysis, DNA cloning, and DNA fingerprinting using the polymerase chain reaction (PCR). Advanced techniques include DNA transfection and protein quantitation. In this course safety policies and instructions will be reviewed in the first laboratory; students will be directed to read lab safety regulations. In addition, general laboratory practices and specific Molecular and Cell Biology procedures and techniques will be discussed.

LEARNING OBJECTIVES (Gen Ed):

Upon completion of the lab, the students will be able: 1. To learn to be observant and to develop and sharpen those observational and critical thinking skills

through inquiry. 2. To discipline yourself to develop good record-keeping skills, required to be successful in any career you

plan to pursue. 3. To learn to think analytically about the observations you have made, and to be able to analyze a problem

and focus on a hypothesis to be tested. 4. Determine the best way of testing the hypothesis, and using creativity to solve problems, including

interpretation of data. 5. To communicate your findings about the processes studied and results obtained in ways appropriate to the

biological sciences, both in written and oral formats. 6. To work on collaborative projects and also in teams.

ASSESSMENT OF STUDENT LEARNING (Laboratory Grading Policy)

1. The Notebook and Report (15 % of the lab grades) – Students are required to have a laboratory notebook, where they will record all observations, measurements, and other experimental details during the lab period. The notebook will be checked periodically by the instructor.

2. Scientific Report (10 % of the lab grade) – A typed report, written in the style of a scientific paper, is due no later than two weeks before the end of the semester. The standard format for writing a scientific research article will be provided, in which the author has to present the research in an orderly and logical manner.

31

3. Project Presentation (15 % of the lab grades) – Group of 4-5 students will work on a project and present their project at the end of the semester. By the third week of the course groups will be formed and each group would be assigned a project.

4. Quizzes (60% of the lab grade) – 4 quizzes (15 % each quiz).

TOPICAL LABORATORY OUTLINE

Week Laboratory

1.

Introduction to Techniques -Data collection in laboratory environment -Discussion of group projects -Principles for safety in the laboratory -Review of basic molecular genetic techniques including micro-pipetting, electrophoresis etc.

2. Study of Eukaryotic Cells -Microscopy - Students will be paired off and given the Cell Scavenger Hunt Handout, which they will complete by utilizing the Internet.

3.

Quantitative Determination of Proteins - Determination of protein concentration by the Lowry method

Quiz 1

4.

Protein Purification - Purification of protein - Enzyme assays

5. Protein Characterization

"SDS Poly Acrylamide Gel Electrophoresis” (PAGE)

6. Isolation of Plasmid DNA

7. Characterization of Plasmid DNA

Quiz 2 8. Restriction Mapping of Lambda DNA

9. Restriction Mapping of Lambda DNA continued

10. DNA Recombination and Transformation

11. DNA Recombination and Transformation continued

Quiz 3 12. Polymerase Chain Reaction (PCR)

13. Analysis of PCR products and discussion of RT-PCR

14. Cell Cycle

-Introduction to Modeling the Cell Cycle

15. Student Presentations Quiz 4

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PROPOSAL FOR NEW COURSE

COMPUTATIONAL GENOMICS



Course Information Course title: Computational Genomics Course code: BIO 3354 Credit Hours: 3 credit hours

3 hours lecture per week for 15 weeks Prerequisite: BIO 3350 Text: “Next Generation Microarray Bioinformatics” by Wang, Junbai; Tan, Aik Choon; Tian,

Tianhai (Eds.) 2012 (Humana Press) Course Catalog Description:

Covers selected advanced topics in computational genomics. Modern DNA microchips enable measurement of the activity state of tens of thousands of genes in a cell, and related techniques are being developed for measuring the protein contents. In this course students will utilize modern statistical and computational methods to understand biological processes. This course emphasizes studies of gene and cell function made possible by recent advances in measurement technology, statistical and computational methods.

Additional Reading: “Advanced analysis of gene expression microarray data,” by Aidong Zhang, World Scientific 2006, ISBN 981-256-645-7. “Analysis of Biological Networks,” by Junker, Bjorn & Schreiber, Falk, Wiley-Interscience, 2008, ISBN: 978-0470041444. In addition, materials from recent scientific literature will also be used.

Proposer Information Name: Dr. Walied Samarrai Phone: (718)2605289 Email: [email protected]


Recent developments in biotechnology have enabled large-scale DNA sequencing and high-throughput measurement of several cellular phenomena such as gene expression, protein-protein interactions and protein localization. These technologies have generated an unprecedented amount of data that contains rich information about gene function and systems-level organization of the cell. The tremendous amount of data presents an exciting opportunity for researchers to use tools for interpreting and integrating the data to make inferences about cellular function. This course gives an introduction to various types of functional genomic data available and current computational and statistical methods used for analyzing the data to answer questions in functional genomics and systems biology. In this course students will utilize modern statistical and computational methods

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to understand biological processes. This course emphasizes studies of gene and cell function made possible by recent advances in measurement technology, statistical and computational method. We will cover the analysis of gene expression data, proteomic data, and interaction data, with a special focus on how they can be used to understand and infer networks.

The objective of this class is to prepare students for undertaking bioinformatics research that is biologically driven and develop their skills for critical evaluation of computational biology literature. The specific goals for students include:

1. To acquire a solid background in fundamental concepts of functional genomics and systems biology. 2. To learn current computational methods for biological data analysis. 3. To develop a general understanding of the current state of the functional genomics field, and learn how to

formulate and solve current biological questions with computational methods.

LEARNING OBJECTIVES

Upon completion of this course students will:

1. Gain an understanding of computational tools needed for a wide range of genomics problems. 2. Be able to work in interdisciplinary teams of biologists, biochemists, medical researchers, geneticists, and

computer engineers. 3. Perform genomic comparisons, display genes and large genomic regions in Genome Browser. 4. Be able to discuss gene expression, and the current state of understanding of the mechanisms controlling

regulation of gene expression. Understand computational methods for analysis of microarray technologies, and interpretations of gene expression from this data.

5. Present their data and results in probabilistic terms using statistical significance. 6. Perform sophisticated searches over enormous databases to interpret their results.


LEARNING OUTCOMES ASSESSMENT Discuss microarray technology and microarray experiments

Short answer quizzes, essay type biweekly assignments, and short answer exam questions.

Critically evaluate basics of data analysis and descriptive statistics.

Evaluation of narrative in the semester long research project, essay type biweekly assignments, and exam questions.

Discuss pitfall of microarray technology Essay type biweekly assignments and Evaluation of narrative in the semester long research project

Be able to process and analyze microarray data Semester long research project and essay type biweekly assignments.

Critically evaluate cluster analysis in microarray experiment.

Evaluation of data and the narrative in the research project and essay type biweekly assignments. Short answered exam questions.

Discuss probabilistic modeling in computational genomics.

Short answer quizzes, essay type exam answers and essay type biweekly assignments.

Critically analyze and interpret data obtained from analysis of microarray data.

Evaluation of data in a project paper, and assignments.

Express scientific ideas in a clear, concise, logical Evaluation of the semester long project using rubrics

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and accurate manner and essay type bi-weekly assignments Conduct a literature survey using refereed journals and other sources of scientific information and evaluate their reliability.

Incorporate the concepts taught in the lecture into bi-weekly assignments and semester long project. Ability to write a research paper following a peer reviewed journal format

Evaluation of the essay type biweekly assignments and semester long research project using rubric

Formulate and plan a project report and write research paper using appropriate experimental data, correct scientific language, spelling and grammar; written in a clear, concise, logical and accurate manner.

Evaluation of essay type biweekly assignments and semester long research project using rubric


Week Lecture

1 Primer on Molecular Genetics: Gene, Gene Expression, Central Dogma, cDNA, Hybridization,

2 Microarray Technology: Principle of Microarray, Oligonucleotides, Importance of Microarray, Applications of Microarray, affymetrix GeneChips, Spotted cDNA Arrays, Spotted vs. Affymetryx arrays,

3 • Microarray Experiments: how microarray works, selection of probe, perfect match and

mismatch, affymetrix probe set, DNA microarray, cDNA microarray, current profile of microarray laboratories.

4

Basics of Data Analysis and Descriptive Statistics: Typical clinical study, Typical genetic study, Steps of reasoning (scientific method), Variables, Descriptive statistics (frequency count, relative frequencies, cumulative frequencies, histogram, boxplots, variance and so on)

Exam 1

5 Preprocessing of Microarray Data: Biological question, differentially expressed genes, experimental design, microarray experiment, image analysis, image processing, normalization, biological verification

6 R and Bioconductor: What R does and does not, R and Statistics, R as calculator, variables in R, functions and operators, vectors, matrices and arrays,

7 Resampling and Bootstrap: bootstrap test; bootstrap analysis, permutation algorithm for obtaining p-value

Exam 2

8 Identification of Differentially Expressed Genes: Qualitative factors, quantitative factors, gene selection, classical parametric statistics t-test, requirements of t-test, permutation algorithm for obtaining p-value

9 Cluster Analysis in Microarray Experiments: clustering algorithms, cluster analysis package in R, partition method K-means clustering, K-means clustering in R, partitioning around medoids, hierarchical methods

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10

Classification in Microarray Experiments: classification of samples, classification of genes, model construction, model usage, evaluation of classification methods, quality of prediction, performance assessment, nearest neighbor classifier, centroid classification, Bayesian classification,

11 Probabilistic Modeling: basic probability rules, application of Bayesian classifier, Bayesian formalism, independence assumption

Exam 3

12 Identification of Transcriptional Binding Site: genome sequencing, gene regulation, transcriptome of DNA microarray, mechanisms of transcriptional regulation, databases for identifying binding sites,

13 Genomic Data Mining: Support Vector Machines, linear learning machine, large margin decision boundary, perceptron, non linear classifiers

14 Computational Discovery of Genetic Functional Modules:


GRADING PROCEDURE: 1. 4 exams = 60% (each exam will be 15 % of final grade) 2. Project = 20 % 3. Weekly and biweekly assignments = 10% 4. Participation* = 10%

*Participation Participation is key to making the experience of everyone a pleasant one. However participation does not just mean that student should be present, but it means that the student should:

• Reviews all course sections and completes all weekly and biweekly assignments on a timely basis, • Ask questions about the topic and evaluate the topic presentations. • Actively and interactively participate in each lecture’s discussion in the classroom and online. This

requirement applies to students whether they are taking the course online or face to face.

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NEW COURSE PROPOSAL

MOLECULAR MODELING IN BIOLOGY



Course Information Course title: Molecular Modeling in Biology Course code: BIO 3356 Credit Hours: 3 credit hours

3 hours lecture per week Prerequisite: BIO 3350 Text: 3. Molecular modeling by Andrew R. Leach. Prentice Hall. 2nd ed. (2001)

4. Modeling Biological Systems: Principles and applications by Haefner James W, Springer Publisher, 2nd ed. (2005)

Course Catalog Description:

This course covers the applications of computer modeling and simulation to problems involving biological macromolecules. The targeted areas are in protein structure modeling, structure-based drug design, drug screening, cheminformatics, and intermolecular interactions and binding. Students will learn the theory and algorithms underlying a variety of simulation techniques.

Additional Reading: Research papers and lecture notes will be provided by the instructor. In addition, the following websites will serve as supplementary text:

http://cacs.usc.edu/education/cs653_s06.html http://www.ch.embnet.org/MD_tutorial/ http://swift.cmbi.ru.nl/gv/dssp/ (DSSP) http://searchlauncher.bcm.tmc.edu/seq-search/struc-predict.html (BSM) http://npsa-pbil.ibcp.fr/cgi-bin/npsa_automat.pl?page=/NPSA/npsa_seccons.html http://swissmodel.expasy.org/ http://us.expasy.org/

Proposer Information Name: Prof. Isaac Barjis Phone: (718) 260-5285 Email: [email protected]


This course covers the applications of computer modeling and simulation to problems involving biological macromolecules. The targeted areas are in protein structure modeling, structure-based drug design, drug screening, cheminformatics, and intermolecular interactions and binding. Students will learn the principles and applications of each of the algorithms and programs used in structure modeling. Take home assignments &

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exercises and a semester long research project will provide experience with software presently used in the field. Topics examined in detail include: discrete and continuous model; computational tools; molecular visualization; simulation methodology; force field methods; optimization; experimental design; docking; structure databases; and refinement and prediction of structures. Popular software programs used in industry will also be covered including: protein-ligand (drug) binding (AUTODOCK, DOCK), general packages aimed at structure modeling (SYBYL, QUANTA, INSIGHT II), and molecular dynamics simulations (CHARMm, AMBER).

LEARNING OBJECTIVES

Upon completion of the course, students will be able to demonstrate: • Mastery of basic techniques used in the modeling of biomolecular systems; • Fluency in translating biological ideas into mathematical models and mathematical meaning into their

respective biological expressions; • Ability to analyze performance and scalability in MD simulations.


LEARNING OUTCOMES ASSESSMENT Differentiate between stochastic, discrete and continues models

Evaluation of narrative in the research paper, short answer quizzes, and exam questions.

Critically evaluate biological process and be able to model and analyse a given biological process.

Evaluation of narrative in the project design, essay type biweekly take home assignment , and exam questions

Discuss the need for modelling and their pitfall Short answer, and essay type answer quizzes and exams. Evaluation of project and research paper

Use www to predict protein 3-D structure Semester long research project where students will pick a specific sequence from the protein family (available at www) and model the structure of that sequence using the techniques and tools you acquired during the course (tools are available at www).

Critically evaluate challenges faced in prediction of protein structures

Essay type biweekly take home assignment, short answer quizzes and exams. Evaluation of data and the narrative in the research paper

Learn rules for efficient design and modeling of biological process/system biology

Essay type biweekly take home assignment and evaluation of research project.

Critically analyze and interpret data obtained from a model

Evaluation of data and model in a project project.

Express scientific ideas in a clear, concise, logical and accurate manner

Evaluation of the semester long project using rubrics.

Conduct a literature survey using refereed journals and other sources of scientific information and evaluate their reliability.

Incorporate the concepts taught in the lecture into bi-weekly assignments and semester long project. Ability to write a research paper following a peer reviewed journal format

Evaluation of the assignments and project using rubric; Essay type biweekly take home assignment.

Formulate and plan a project report and write research paper using appropriate experimental data, correct scientific language, spelling and grammar; written in a clear, concise, logical and

Evaluation of Essay type biweekly take home assignment and semester long project using rubric.

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accurate manner.


Week Lecture 1 Introduction. What is a model? Why are models useful? Modeling approaches and pitfalls.

2 • The modeling process: Mathematical methods; Computer models and automata theory; representation of system biology as a model.

3 • Discrete Models

4 • Continuous Models Exam 1

5 Molecular Mechanical Force Field: Quantum mechanics; Empirical force field; statistical potential (flexible); molecular mechanics

6 Statistical Potentials: Knowledge based potential; potential of mean force; atomic potential; protein-protein binding potential; protein –DNA statistical binding potential

7 • Conformational Analysis: conformation search; systematic search (grid search); random

search; clustering; search of global minimum Exam 2

8 Computer simulation: Time averages and ensemble averages; calculation of simple thermodynamic properties (energy, heat capacity, pressure, temperature); practical aspect of computer simulations; predict boundary conditions;

9 Monte Carlo simulation: introduction; canonical ensemble; simple Monte Carlo; Metropolis method; models used in polymers

10 • Molecular Dynamics Simulation: Overview; effect of time step on properties; setting up

and running simulation; equilibration and production; time dependent properties; problem with cutoffs

11 • Structure Modeling: Protein structure; Secondary structure prediction; protein folding;

Exam 3

12 • Structure Modeling: Protein folding and unfolding; Tertiary structure prediction;

Homology modeling; fold recognition

13 • Protein interactions: Interaction modeling (docking); docking procedure; need for refinement; residual-based potential;

14 Computational drug design


GRADING PROCEDURE: 5. 4 exams = 60% (each exam will be 15 % of final grade) 6. Project* = 20 % 7. Weekly and biweekly assignments = 10% 8. Participation*** = 10%

*Project: This is a semester long project. At the beginning of the semester each student will pick a protein family from the list of available protein families. Then the student will use www to obtain the sequence and other information of given protein. By the end of the semester, the student should be able to model the structure of that sequence using

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the techniques and tools they acquired during the course and complete a full report on the particular protein family. Students will use internet resources as well as computational tools covered in class to cover some of the following areas:

• Protein stability • Conformational changes • Protein structure prediction • Protein interaction prediction • Structure-based function prediction • Molecular dynamics simulations • Monte Carlo simulations

Below is a list of topics/steps final project should contain. Students are supposed to follow all of those steps to complete the project. Each of the steps depends on the previous ones, for example alignment you are going to use to accomplish homology modeling has to be in correlation with the secondary structure prediction and fold recognition, i.e. step 3 should rely on steps 1 and 2.

1. Secondary structure prediction 2. Fold recognition 3. Homology modeling 4. Docking 5. Structure based function prediction

***Participation Participation is key to making the experience of everyone a pleasant one. However participation does not just mean that student should be present, but it means that the student should:

• Reviews all course sections and completes all weekly and biweekly assignments on a timely basis, • Ask questions about the topic and evaluate the topic presentations. • Actively and interactively participate in each lecture’s discussion in the classroom and online. This

requirement applies to students whether they are taking the course online or face to face.

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NEW COURSE PROPOSAL

INTERNSHIP/RESEARCH IN BIOMEDICAL INFORMATICS


School of Arts and Sciences Biological Sciences Department

Course Information Course title: Internship/Research in Biomedical Informatics Course code: MED 3910 Credit Hours: 5 credit hours

225 field hours total, spread throughout the semester or during the summer (for summer internships).

Prerequisites: MED 4229, BIO 3352, and permission of program coordinator. Text: Selected by course coordinator and/or project supervisor to support chosen

project. Course Summary: An internship/research course that exposes majors to the practice of

medical informatics and molecular bioinformatics in commercial, research, and medical settings.



This is an internship and/or research course that exposes students in the program to the practice of medical informatics and molecular bioinformatics in commercial, research, and medical settings. Students will be assisted in identifying viable internships and/or research opportunities in their area of interest. A student log/journal will be kept throughout the duration of the internship or research work. The employer/supervisor evaluation, the student’s log/journal, a written report and an oral presentation will determine the course grade.


Upon satisfactory completion of the course, the student will:

1. articulate a coherent research or project plan, directed at particular aspects of medical informatics and/or molecular bioinformatics.

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2. use knowledge gained in medical informatics and molecular bioinformatics coursework to address a problem or need, as defined by the project plan.

3. recognize the biological and biomedical principles at play in the particular project chosen. 4. use information and computer systems in current use in medical informatics and/or molecular bioinformatics,

as part of a project methodology. 5. keep accurate and meticulous records of research or project activities. 6. demonstrate effective written and oral skills for presenting the results of project activities. 7. communicate effectively with other professionals, including superiors, in a setting resembling real

work/research. 8. produce properly formatted and worded CV and resume, as well as cover letters, and understand the value of

such instruments. 9. gain experience in interviewing for internship or research positions, and understand proper decorum and

accepted practices in the job market.

GENERAL COURSE STRUCTURE

This internship course is the culmination of the study of biomedical informatics, and should serve as a demonstration of the abilities of the students (in terms of knowledge, skills, and values) to function in real-world career and/or research settings. Students enrolled in the course (typically in their last semester in the program) must demonstrate maturity and sophistication in problem solving, time management, and in the use of methods and tools in effective interdisciplinary approaches.

Students, in consultation with the instructor and/or program coordinator, are urged to investigate possible internship options in the New York City or tri-state area, and elsewhere (for summer internships) prior to the internship semester or summer. Contact with the outside internship program must be established by the student, with the assistance of the program coordinator. If necessary, applications have to be submitted in advance, and interviews conducted when invited. Alternatively, for those interested in pursuing careers in medicine, research, or academia, scientific research work with faculty at City Tech or at other academic institutions can fulfill the requirements of the course.

Students are expected to construct a project plan prior to enrollment in the course. The detailed project plan must contain a description of the project and project goals, a time table for each aspect of the project, along with resources needed and other logistical considerations. Any personnel described in the project plan must submit a letter of support, specifying the extent of their involvement and commitment. Resources that will be used (such as funding) must be laid out and properly accounted for. The project plan must be approved by the course instructor or program coordinator before admission to the course.

OPTIONS FOR INTERNSHIP AND RESEARCH

Students can choose an internship or research program in any aspect of biomedical informatics—from medical and health informatics in clinical, medical, or research settings to molecular bioinformatics in academic, commercial, or research settings. Research with faculty (at City Tech or elsewhere) on any relevant biomedical informatics topic is also a possible option. A list of City Tech and other locally based faculty, along with their associated research projects in biomedical informatics, will be made available for the students prior to the semester of enrollment. (Currently, there are five faculty members in the Biological Sciences Department who can potentially advise students in various aspects of computational biology and bioinformatics research work.)

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For the internship option, a number of internship and research opportunities exist for students. A full list of these opportunities, to be kept up-to-date by the program coordinator, should be consulted by prospective students of the course early in the semester prior to the internship semester or summer. The following list, not meant to be comprehensive, gives the range of possibilities. Note that some internships are geared towards minority and underrepresented populations, and are located in the New York tri-state area.

Albert Einstein College of Medicine hosts the Diversity Student Summer Research Opportunity Program, designed to provide educational opportunities for undergraduate students who have a strong interest in a research career in biomedical or biological sciences or medicine. The program provides nine weeks of experience and participation in biomedical research. Students participating in the program will conduct research under the direction of a faculty member. Research assignments will be made based upon availability of research opportunities and according to the mutual interests of the faculty sponsors and student participants. The SPURS Program of Columbia University is designed to expand the pool of medical and biomedical research applicants from diverse and economically disadvantaged groups whose members are presently under-represented in medicine and biomedical research. The SPURS Program provides intensive research fellowship experiences on the campus of Columbia College of Physicians and Surgeons to undergraduate students from local colleges. This comprehensive experience provides meaningful training in biomedical research, and enhances each student’s’ ability to achieve a career in biomedical research and/or medicine by pursuing an advanced degree. In addition to specific training in the indicated research area, the students receive in-depth training and experience in biomedical research methodology. Mount Sinai School of Medicine in New York City offers summer research internships to undergraduate students who are interested in doing research at a leading biomedical institution. The Summer Undergraduate Research Program (SURP) at Mount Sinai is a 10-week program that begins in June every year. SURP fellows receive intensive research training in a cutting-edge biomedical laboratory, thus gaining an insider’s perspective into Mount Sinai graduate programs and academic life. The Access program of Weill Cornell Graduate School of Medical Sciences (WCGS) in New York City is a summer internship program that trains underserved college students in the biomedical sciences. Interns gain hands-on experience in a biomedical research laboratory and are encouraged to apply to PhD programs. Selected students are placed in laboratories at the WCGS under the mentorship of experienced faculty members. In addition to the laboratory experience, students attend lectures and discussions aimed at enhancing their understanding of the current status of biomedical research, the pathways available for entering research careers, and the range of available career opportunities. Students also participate in weekly journal clubs, attend workshops that teach them how to prepare for interviews and seminars, and take part in social activities. The Summer Research Program offered by the Office of Minority Affairs of SUNY Downstate (Brooklyn, New York) is designed for undergraduate students who have historically been underrepresented in the biomedical professions (African American, Mainland Puerto Rican, Native American and Mexican American). The program provides eight (8) weeks of experience and participation in biomedical research. In addition, students will participate in a weekly seminar lecture series. Students participating in the program will conduct research under the direction of a faculty member. Research assignments will be made based upon availability of research opportunities and according to the mutual interests of the faculty sponsors and student participants. Participants will have the opportunity to interact not only with the faculty members directing the research, but also with the medical/graduate students working at the site. A final abstract submission and oral presentations are requirements for completion of the summer program. The Summer Undergraduate Research Fellowship (SURF) Program at Boston University (Massachusetts) is designed to promote access to graduate education for talented undergraduate students, especially those from minority groups traditionally underrepresented in the sciences: African-American, Hispanic, Native American/Native Alaskan, and Pacific Islander/Native Hawaiian/Polynesian. The SURF Program is supported by funds from the National Science Foundation (NSF-REU; NE-AGEP), the Department of

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Defense (ASSURE), and Boston University. The program is open to non-Boston University students who wish to conduct research in the sciences, technology, or engineering. The program consists of ten weeks of full-time research in a Boston University lab, mentored by a faculty member. Biomedical Informatics Internship Program at the Department of Biomedical Informatics at Vanderbilt University (Nashville, Tennessee). The program anticipates having a number of funded short-term internship positions for students through an NIH/National Library of Medicine summer research experience grant. This program is designed to expose young scholars to the field of biomedical informatics through faculty-mentored projects that apply information technology to address health care challenges. The Informatics Education Division of the Center for Biomedical Informatics (CBMi) at the Children’s Hospital of Philadelphia (Pennsylvania) supports an internship program that allows undergraduate and graduate students studying informatics-related fields to experience biomedical informatics within an established, world-class research center. CBMi's combination of academic research and commercial service activities provides a unique learning experience for students. CBMi offers ongoing paid and unpaid internships through its collaborations with Drexel University, Temple University, and The University of Sciences in Philadelphia, as well as a growing number of other institutions.

GRADING PROCEDURE

Students will be evaluated based on the following criteria: an initial evaluation of the research or project plan, to be conducted by the course instructor or program coordinator (a short write-up is required); the quality and completeness of a student log/journal; project supervisor evaluation of student performance during the project span; a final written report, upon completion of the project; and an oral presentation in the presence of the City Tech community. The course instructor will assign the grades for each component (except for the supervisor evaluation), in consultation with the project supervisor as well as other involved program faculty.

The numerical breakdown of the components of the final grade is as follows: • Research Plan 15% • Student journal and midterm progress report 20% • Supervisor evaluation 30% • Final written report 20% • Oral presentation 15%

STUDENT LOG/JOURNAL

The student log/journal is an integral part of the internship course. The journal, in electronic form (a private blog, or a restricted access website), is to be kept current and relevant by the student, containing his/her activities related to the project, raw data, preliminary analysis, and resources and literature encountered along the way. In addition, the journal should contain reflections by the student about the progress of the project, in light of the project plan. The journal should also log official communication between the student and others that are directly related to the project.

FINAL PROJECT REPORT AND ORAL PRESENTATION

The final project report, which accounts for 35% of the final grade, involves: (1) a formal write-up (20%) of at least 12 pages (not including the cover page), using 1.5 line spacing (not double spaced); and (2) a 45-minute formal oral presentation, to be delivered at the end of the semester (or at the beginning of the fall semester following the summer internship), with an audience consisting of other students in the program, City Tech faculty, and others involved and/or interested in the project topic (15%).

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APPENDIX B: COURSE DESCRIPTIONS FOR EXISTING

UPPER LEVEL COURSES FOR THE PROGRAM

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COURSE DESCRIPTIONS FOR EXISTING UPPER LEVEL COURSES FOR THE PROGRAM

BIO 2311 Human Anatomy and Physiology ISCI Core 3 cl hrs, 3 lab hrs, 4 cr The anatomy and physiology of the cell, tissues, skeletal, muscular and nervous systems. Prerequisites: 1) BIO 1101, or College-level general biology course with lab or a score of 85 or above on the New York State Regent’s exam; and 2) CUNY proficiency in reading and writing

BIO 2312 Human Anatomy and Physiology IISCI Core 3 cl hrs, 3 lab hrs, 4 cr A study of the circulatory, respiratory, digestive, urinary, endocrine and reproductive systems; intermediary metabolism, electrolyte and water balance. Prerequisite: BIO 2311

BIO 3350 Elements of Bioinformatics SCI Core 2 cl hrs, 4 lab hrs, 4 cr This course develops awareness of Internet-based information, and encourages exploration and use of the wide range of databases available to those working in the fields of Biology, Biotechnology and the Pharmaceutical industries. Different tools and computational methods are used to analyze DNA, RNA and protein structures. The course is designed to meet the increasing demand for individuals skilled in using computers to manipulate and analyze the growing quantities of genetic information available to bioscientists and the medical profession. Note: This course can fulfill the general education requirements for Science II (in place of BIO 1201). Prerequisites: MAT 1275, BIO 1101 and CUNY proficiency in reading and writing

BIO 3526 Pathophysiology 3 cl hrs, 3 cr This course applies knowledge of normal anatomy and physiology to promote a clear understanding of disease processes. It introduces the student to the common body responses and manifestations of disease that result from imbalances in homeostasis of the body. The course addresses common well defined alterations involving cellular proliferation, mobility, neurology, digestion, circulation and immunity. Prerequisites: CHEM 1110, BIO 2312

BIO 3601 Biochemistry 3 cl hrs, 3 lab hrs, 4 cr This course adopts an interdisciplinary approach to understanding the fundamentals of biochemistry, including an introduction to the basic concepts and most common research methods. The focus will be upon the major macromolecules and chemical properties of the living systems. The goal is the development of an integrated appreciation

of how biomolecules act and interact to catalyze reactions, to synthesize and degrade biomolecules, and utilize or release energy. Both catabolic and biosynthetic pathways will be discussed. The biochemistry underlying the conversion of information contained in DNA to cellular macromolecules through replication, transcription and translation will be covered. Primary topics include the structure, function and metabolism of amino acids, proteins, carbohydrates, nucleic acids and lipids; the physical properties of water, pH, buffers and enzyme kinetics; DNA replication and gene regulation. Prerequistes: BIO 1101, MAT 1275, ENG 1101 and CHEM 2223

CHEM 2223 Organic Chemistry I 4 cl hrs, 3 lab hrs, 5 cr An introduction to the fundamental concepts of nomenclature, structure, functional group chemistry, and reaction mechanisms of organic compounds. Topics include the chemistries of alkanes and alkyl halides, stereochemistry, and SN1, SN2, E1, and E2 mechanisms. Laboratory exercises illustrate methods of preparation and measurement of organic compounds. Prerequisite: CHEM 1210

CHEM 2323 Organic Chemistry II 4 cl hrs, 3 lab hrs, 5 cr The second part of a two-semester sequence in organic chemistry. Topics include the chemistries of alcohols, ethers, conjugated and aromatic compounds, carbonyl compounds, and amines. The oxidation-reduction chemistry of organic compounds and properties of carbohydrates, amino acids, proteins, and nucleic acids are introduced. Laboratory work stresses the preparation and spectroscopic characterization of organic compounds. Prerequisite: CHEM 2223

MAT 1575 Calculus II MATH Core 4 cl hrs, 4 cr A continuation of MAT 1475. Topics include Taylor polynomials, Mean Value Theorem, Taylor and Maclaurin series, tests of convergence, techniques of integration, improper integrals, areas, volumes and arclength. Prerequisite: MAT 1475

MAT 2440 Discrete Structures and Algorithms I MATH Core 2 cl hrs, 2 lab hrs, 3 cr

This course introduces the foundations of discrete mathematics as they apply to computer science, focusing on providing a solid theoretical foundation for further work. Topics include functions, relations, sets, simple proof techniques, Boolean algebra, propositional logic, elementary number theory, writing, analyzing and testing algorithms. Prerequisites: CST 2403 and MAT1375

MAT 2540 Discrete Structures and Algorithms II 2 cl hrs, 2 lab hrs, 3 cr This course continues the discussion of discrete mathematical structures and algorithms introduced in MAT 2440. Topics in the second course include predicate logic, recurrence relations, graphs, trees, digital logic, computational complexity and elementary computability. Prerequisite: MAT 2440; Pre- or corequisite: CST 3503

MAT 2572 Probability and Mathematical Statistics I 4 cl hrs, 4 cr The study of discrete and continuous probability distributions including the Binomial, Poisson, Hypergeometric, Exponential, Chi-Squared and Normal Distribution. Conditional distributions, covariance and correlation, confidence intervals, least square estimation, chi-square goodness of fit distribution and test for independence and randomness. Ends with an application to queuing. Prerequisite: MAT 1575

MAT 2580 Introduction to Linear AlgebraMATH Core 3 cl hrs, 3 cr An introductory course in Linear Algebra. Topics include vectors, vector spaces, systems of linear equations, linear transformations, properties of matrices, determinants, eigenvalues and eigenvectors. Pre- or corequisite: MAT 1575

MAT 2675 Calculus III MATH Core 4 cl hrs, 4 cr A continuation of MAT 1575. Topics include polar and parametric equations, vectors, solid analytic geometry, partial derivatives, multiple integrals, vector fields, line integrals and Green’s Theorem. Prerequisite: MAT 1575

MAT 2680 Differential EquationsMATH Core 3 cl hrs, 3 cr Topics include methods of solving ordinary differential equations and applications to various problems. Prerequisite: MAT 1575

MAT 3672 Probability and Mathematical Statistics II 4 cl hrs, 4 cr The study of multivariate normal distribution, the distribution of transformed vectors and order statistics. Includes generating functions, t- and F- distributions, central limit theorem, hypothesis testing, multiple regression, statistical inference for regression, diagnostic testing and design of experiments. Prerequisites: MAT 2572, MAT 2580, MAT 2675

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MAT 3772 Stochastic Models 3 cl hrs, 3 cr The use of discrete and continuous distributions to construct deterministic and stochastic simulation models. Stochastic simulations may include Markov Processes, M/G/I Queuing Systems, Monte Carlo Simulation and Analytic Simulation. Prerequisite: MAT 2572

MAT 4872 Probability and Mathematical Statistics III 4 cl hrs, 4 cr The study of exponential distribution and reliability and failure rates. Hypo- and Hyperexponential, Erland, Gamma and Weibull distributions. Expectation of multiple random variables and the computation of mean time failure. Transition probabilities and time birth-death process. Least squares curve fitting and analysis of variance. Prerequisite: MAT 3672

HSA 3510 Health Services Management I 3 cl hrs, 3 cr Systems for the delivery of health services and related issues will be examined. The course will explore the present and probable future of the industry including the historical shift from a policy system to a market-driven system. Classes are forums of discussion emphasizing contemporary issues related to health care professionals, facilities and organization patterns of both the system and related suppliers and industries. Prerequisite: Admission to the Health Services Administration program or department approval

HSA 3560 Legal Aspects of Health Care 3 cl hrs, 3 cr This course will explore ethical and legal issues and their interaction in today’s dynamic health care arena. By studying legal principles, decision-making and cases, students will learn to understand, integrate and apply these disciplines in the health arena. Pre- or corequisite: HSA 3510

HSA 3602 Health Services Management II 3 cl hrs, 3 cr Through analysis, discussion and problem-solving in a seminar format, this course will acquaint the student with issues that have an impact on their profession, the health care industry and their role as managers. Prerequisites: HSA 3510

HSA 3630 Health Care Finance and Accounting Management 3 cl hrs, 3 cr This course is designed to develop the decision makers’ understanding and management of financial information in the health care industry. Emphasis will be placed on concepts that will allow students to understand the huge, complex, and in many ways unique, health care industry.

Prerequisites: HSA 3510, MAT 1175 or MAT 1180

HSA 4620 Health Care Information Systems 3 cl hrs, 3 cr This course will provide an in-depth view of the information technology used by the health care industry. HSA 4620 will examine all the components that make up the clinical and administrative information systems in health care organizations and will give students the information needed to participate in decisions regarding appropriate systems selection and management. Prerequisites: HSA 3510, computer literacy or MST 1101

CST 1204 Database Systems Fundamentals 2 cl hrs, 2 lab hrs, 3 cr This course will introduce the student to ANSI standard Structured Query Language (SQL). The course will cover the various syntax that governs this language. In-depth discussions and practice will be given so that the student will be able to manipulate (insert, update, delete and retrieve) data in a relational database. Prerequisites: CST 1100 and CST 1101

CST 1215 Operating Systems Fundamentals 2 cl hrs, 2 lab hrs, 3 cr Introduces basic concepts and structures of operating systems, and how computer operating systems allocate resources. Provides basic working knowledge of computer operating system commands, functions, and management approaches using the DOS, Windows, Linux and UNIX operating environments. Topics include: memory management, process management, device management, file management and operating system tools. Introduces command structures and explores operations using GUI and Command Language Interfaces. Prerequisites: CST 1100, CST 1101

CST 2307 Networking Fundamentals 2 cl hrs, 2 lab hrs, 3 cr Introduces fundamental computer networking concepts and skills. Provides instruction in networking media, physical and logical topologies, and common networking standards and protocols. Conceptual framework of the OSI model, and its implementation with the TCP/IP and other network protocols. Both networking design and analysis methods. Provides knowledge necessary to design, install, configure and support network infrastructure effectively. Networking administration skills are developed for different operating systems. Prerequisite: CST 1215

CST 2309 Web Programming I2 cl hrs, 2 lab hrs, 3 cr This course focuses on how to design and maintain interactive and dynamic websites using HTML, Cascading Style Sheets (CSS)

and client-side scripting with JavaScript. The students will also learn basic Web Page design principles. The goal is to develop effective, pleasing and useful websites. In the JavaScript part of the course, students will develop real-world projects to learn JavaScript programming, the JavaScript Object Model, JavaScript event handlers and how to integrate JavaScript programs in an HTML document. Students will apply this knowledge to create pop-up windows and scrolling messages as well as to validate forms and enhance the use of images and form objects. Client-side scripting technology will also be used to create cookies and shopping cart applications. Prerequisites: CST 1201

CST 2403 Introductory C++ Programming Language Part I 2 cl hrs, 2 lab hrs, 3 cr This course is an intensive introduction to computer programming intended for CIS majors. Initial topics include the implementation in the C++ language of data types, operations, expressions, decision statements and loops. Other topics include functions and subprogram structure, pointers, arrays and structures. The course will teach the fundamental programming assignments aimed at reinforcing the material covered in class. Prerequisites: CST 1101 and MAT 1275 or higher or MAT 1476

CST 2406 Introduction to Systems Analysis and Design3 cl hrs, 1 lab hr, 3 cr An introduction to systems analysis and design concepts and tools including the three basic phases of the System Development Life Cycle: system analysis, system design and system implementation and maintenance. CASE tools are introduced to perform data-process modeling. Prerequisites: CST 1201, CST 1204

CST 2409 Web Programming II2 cl hrs, 2 lab hrs, 3 cr This course focuses on how to design and maintain interactive and dynamic Web applications using server-side scripting. Students learn server-side scripting by using Hypertext Preprocessor (PHP) language. Students install and configure a Web server (Apache), PHP, and an open-source relational database (MySQL). Additionally, students also learn in PHP how to add functions and control structures, manipulate strings, access files and directories, manipulate data arrays, work with MySQL databases, save state information using hidden form fields, query strings, cookies and sessions. In addition, students learn how to include object-oriented programming techniques in PHP scripts, and learn techniques used to trace and resolve errors in PHP scripts. Other sever-side technologies (ASP, Cold Fusion) are also introduced. Prerequisite: CST 1204, CST 2309

47

CST 3503 C++ Programming Part II 4 cl hrs, 3 cr This course is an intensive description of object-oriented programming intended for BTech majors. Central to this object orientation is the concept of a class, which is a programmer-defined data type. Initial topics include implementation in the C++ language. The construction of class is based on both structures and functions, member functions, friend functions, operator overloading. Other topics include inheritance, virtual functions and polymorphism and class templates. Prerequisite: CST 2403

CST 3504 Design of Microcomputer Databases 2 cl hrs, 2 lab hrs, 3 cr This course provides a general introduction to database design. The three main phases in database design are covered; conceptual, using Entity Relational Diagram (ERD) and Unified Modeling Language (UML); logical, using relational model; and physical, using a Database Management System. The basics of relational data modeling (concepts of relation, attribute, primary key and foreign key) are reviewed, and mapping the conceptual model to the relational model is discussed. Advanced concepts of relational theory normalization and denormalization are included. Physical implementation is described with the help of a particular Relational Database Management System (RDBMS). The students must be familiar with SQL. Prerequisites: (MST 2304 or CST 1204) and CST 2406

CST 3510 Computer Security 2 cl hrs, 2 lab hrs, 3 cr This course is a practical guide to security issues facing computer professionals today. Students will acquire the knowledge and skills to maintain the integrity, authenticity, availability and privacy of data. It covers computer viruses, authentication models, certificates, group policy, cryptography and access control. It also introduces the fundamental security issues of programming, database and web server. Other topics include how to monitor the system for suspicious activity and fend off attacks, keep spies and Spam out of email, take ultimate control of security by encrypting data, design Active directory, blocking ports and locking down the registry. Prerequisites: MST 2307, MST 2405

CST 3513 Object Oriented Programming in Java 2 cl hrs, 2 lab hrs, 3 cr This course introduces fundamentals of object-oriented programming (OOP). Through intensive lab assignments, students will master the concepts and implementation of objects and classes, inheritance and polymorphism, abstract classes and interfaces. Building upon fundamental concepts of computer programming, students will implement OOP in the Java

programming language, and learn to create GUI applications – basic event driven programming. Exception handling also will be introduced. Prerequisite: CST 1201 with a grade of C or higher

CST 3603 Object-Oriented Programming 2 cl hrs, 2 lab hrs, 3 cr This course introduces students to the powerful Visual C++ .NET with Visual Studio and the .NET platform and to Microsoft’s Windows integrated development environment. The extensive coverage of Graphical User Interface will give students the tools to build compelling and fully interactive unmanaged and managed application programs. The course will introduce the concepts implemented with managed code that enables Visual C++ .NET to use .NET framework class libraries that are shared among Microsoft’s .NET languages. This course also will teach students to understand basic database model and queries, to understand and use ADO.NET’s model and to use classes and interfaces of namespace System::Data and System::Data::OleDb to manipulate. Prerequisite: CST 3503

CST 3604 Design of Distributed Databases 2 cl hrs, 2 lab hrs, 3 cr This course is a continuation of the course “Design of Microcomputer Databases” (CST 3504). It concentrates on the physical design of databases, as well as the general introduction to the design of distributed relational databases. Such problems as database management, query processing, transaction management, reliability and security are discussed. Important issues of physical design including the distribution of the database, are discussed under different architectures of distributed information systems. Such aspects of distributed databases as fragmentation, allocation and replication of data are discussed in detail. The course covers the special problems that occur from the distribution of data semantic control, reliability and transaction management, as well as the techniques used to solve these problems. Prerequisite: CST 3504

MST 1205 Microcomputer Systems 2 cl hrs, 2 lab hrs, 3 cr The operating system is the most fundamental program of any computer. It controls all the computer’s resources and provides the base upon which the application programs can be written. This course provides an in depth study of computer hardware and operating system concepts. Focus will be on the command line interface. Students will problem solve using the command line interface in the Windows environment. Focus will be on command syntax, disk organization, writing simple to complex batch files, troubleshooting and connectivity with local and wide area networks and analysis and backup of the Windows Registry. Prerequisites: CST 1100, CST 1101

MST 2307 Local Area Networks 3 cl hrs, 3 lab hrs, 4 cr Study of the current standard local area network. Basic network concepts and the OSI model are discussed. Topics include topology, servers, workstations, printers and other devices on the LAN, the network operating system, utilities, applications run on the network and LAN management. The network operating system Netware 5.1 is discussed: NDS, network file system, managing users and groups, security, printing, log-in scripts, operating server console. Each student will be given an account with Administrator privileges and will perform network administration tasks. Prerequisites: MST 1205, MAT 1275

MST 2405 Microcomputer Operating Systems 3 cl hrs, 3 lab hrs, 4 cr This is a study of microcomputer operating systems and the usage of selective features of popular microcomputer-based systems. The course introduces the operating systems concepts via study of MS DOS and MS Windows 2000. Main focus will be on Windows 2000 Server OS. Comparison topics cover the file system, processor management, memory management, device management. Other topics will cover multitasking, security, client/server systems, communications and networking support. All concepts will be demonstrated through laboratory assignments. Prerequisites: MST 1205, MST 2307

48

APPENDIX C: PROGRAM SCHEDULING

49

PROGRAM SCHEDULING Term: Fall 1 Check course classification(s) Term: Fall 3 Check course classification(s) Course Number & Title Cr LAS Maj New Prerequisite(s) Course Number & Title Cr LAS Maj New Prerequisite(s) BIO 1101 – General Biology I 4 X X Reading proficiency BIO 3350 – Bioinformatics I 4 X X MAT 1372, BIO

1101 ENG 1101 – English Composition 3 X X MED 4229 – Healthcare Databases 3 X BIO 2312 MAT 1475 – Calculus I 4 X X MAT 1375 HSA 3510 – Health Services Mgmt. I 3 X permission CST 1101 – Problem Solving with

Computer Programming 3 X BIO 3620 – Molecular and Cell Biology 4 X X X ENG 1101, BIO 1101

Term credit total: 14 11 14 Term credit total: 14 8 14 Term: Spring 1 Check course classification(s) Term: Spring 3 Check course classification(s) Course Number & Title Cr LAS Maj New Prerequisite(s) Course Number & Title Cr LAS Maj New Prerequisite(s) BIO 1201 – General Biology II 4 X X BIO 1101 BIO 3352 – Bioinformatics II 4 X X X BIO 3350 CST 1201 – Programming Fundamentals 3 X CST 1101 CST 3504 – Design of Microcomputer

Databases 3 CST 2406, CST

1204 PSY 1101 – Introduction to Psychology 3 X X BIO 3526 - Pathophysiology 3 X X CHEM 1110, BIO

2312 MAT 1372 – Statistics with Probability 3 X X MAT 1375 PHIL 2203 – Health Care Ethics 3 X X ENG 1101 COMM – Speech Communication Elective 3 X LAP Core – Literature/Aesthetics Course 3 X

Term credit total: 16 13 13 Term credit total: 16 13 10 Term: Fall 2 Check course classification(s) Term: Fall 4 Check course classification(s) Course Number & Title Cr LAS Maj New Prerequisite(s) Course Number & Title Cr LAS Maj New Prerequisite(s) BIO 2311 – Anatomy & Physiology I 4 X X BIO 1101 BIO 3354 – Computational Genomics 3 X X X BIO 3350 MST 1205 – Microcomputer Systems 3 CST 1101 ENG 3404 – Literature of Illness and Care 3 X X ENG 1201 or LIT CST 1204 – Database Systems Fundamentals 3 X CST 1101 HSA 4620 – Healthcare Information Systems 3

X

HSA 3510, computer literacy

BS/SS Core – Behavioral/Social Science Core Course 3 X MST 2405 – Microcomputer Operating

Systems 4 MST 1205, MST

2307 ENG 1133 – Specialized Communications

For Tech Students 3 X CST 3604 – Design of Distributed Databases

3 CST 3504

Term credit total: 16 10 7 Term credit total: 16 6 9 Term: Spring 2 Check course classification(s) Term: Spring 4 Check course classification(s) Course Number & Title Cr LAS Maj New Prerequisite(s) Course Number & Title Cr LAS Maj New Prerequisite(s) BIO 2312 – Anatomy & Physiology II 4 X X BIO 2311 BIO 3356 – Molecular Modeling in Biology 3 X X X BIO 3350 CST 2406 – Introduction to Systems

Analysis and Design 3 CST 1101 BS Core – Behavioral Science Core Course 3 X

MED 2400 – Medical Informatics Fundamentals

3 X X BIO 2311 CST 3510 – Computer Security 3 MST 2307, MST 2405

MST 2307 – Local Area Networks 4 MST 1205, MAT 1275

MED 3910 – Internship/Research in Biomedical Informatics

5 X X MED 4229, BIO 3352, permission

Term credit total: 14 4 7 Term credit total: 14 6 8

Program Totals: Credits: 120 Liberal Arts & Sciences: 71 Major: 82 Elective & Other: 38

Cr: credits LAS: liberal arts & sciences Maj: major requirement New: new course Prerequisite(s): list prerequisite(s) for the noted courses

50

http://www.highered.nysed.gov/ocue/lrp/liberalarts.htm�

APPENDIX D: FULL-TIME FACULTY TEACHING ASSIGNMENTS

51

FULL-TIME FACULTY TEACHING ASSIGNMENTS

Faculty Member Name and Title (include and identify Program Director)

Program Courses to be Taught Percent Time to Program

Highest and Other Applicable Earned Degrees & Disciplines (include College/University)

Additional Qualifications: list related certifications/ licenses; occupational experience; scholarly contributions, etc.

Professor Armando D. Solis BIO 3350: Bioinformatics I

80%

Ph.D., Biomedical Sciences (specialization in Biomathematical Sciences), Mount Sinai School of Medicine of New York University

M.S., Chemical Engineering (research in Biochemical Engineering), Yale University

Published a number of articles in top peer-reviewed journals in the fields of Bioinformatics and Computational Biology.

Invited referee for many top journals in Bioinformatics, Molecular Biology, and Computational Biology; and for NSF grants.

Course Fellow in Biomedical Informatics at the Marine Biological Laboratory in Woods Hole, Massachusetts (2011), sponsored by the National Library of Medicine of the National Institutes of Health.

BIO 3352: Bioinformatics II BIO 3354: Computational Genomics BIO 3356: Molecular Modeling in Biology MED 2400: Medical Informatics Fundamentals MED 3910: Internship/Research in Biomedical Informatics BIO 3601: Biochemistry

Professor Isaac Barjis BIO 3350: Bioinformatics I

80%

Ph.D., Bioinformatics MS Bioengineering from University of Illinois at Chicago

Published more than 20 peer-reviewed research articles in the field of Systems Biology and Bioinformatics.

Founding chair of Bioinformatics workshop within the International Summer Computer Simulation

Invited associate editor of Journal of Simulation.

Invited Speaker/Presenter at a number of workshops and international conferences.

BIO 3352: Bioinformatics II BIO 3354: Computational Genomics BIO 3356: Molecular Modeling in Biology MED 4229: Healthcare Databases BIO 3526: Pathophysiology MED 3910: Internship/Research in Biomedical Informatics

Professor Vasily Kolchenko BIO 3350: Bioinformatics I 80%

M.D./Ph.D., Kiev Medical University, Ukraine

Published number of peer-reviewed articles in the field of BIO 3352: Bioinformatics II

52

BIO 3354: Computational Genomics Bioinformatics.

Adjunct faculty in Bioinformatics at NYU Poly.

BIO 3356: Molecular Modeling in Biology BIO 3526: Pathophysiology BIO 2311 Anatomy and Physiology I BIO 2312: Anatomy and Physiology II

Professor Walied Samarrai BIO 2311 Anatomy and Physiology I

50%

Ph.D., Molecular Biology, City University of New York

Published number of peer-reviewed articles in the fields of Bioinformatics and Nanotechnology.

Published peer-reviewed articles in Journal of Bacteriology (highly respected and ranked journal in the field).

Founder of Virtual cell in Second Life.

BIO 2312: Anatomy and Physiology II BIO 3620: Molecular and Cell Biology BIO 3354: Computational Genomics

Professor Laina Karthikeyan BIO 3620: Molecular and Cell Biology

50%

Ph.D., Molecular Biology, New York University Medical Center

Published a number of peer-reviewed research article in the field of Molecular Biology.

BIO 2311 Anatomy and Physiology I BIO 2312: Anatomy and Physiology II BIO 3601: Biochemistry

Professor Selwyn Williams BIO 3620: Molecular and Cell Biology

50%

Ph.D., Biology, City University of New York

Published articles in top peer-reviewed journals in the field of Cell Biology.

Director of Undergraduate Research at City Tech.

Visiting Research Collaborator in Molecular Biology at Princeton University.

BIO 2311 Anatomy and Physiology I

BIO 2312: Anatomy and Physiology II

BIO 3601: Biochemistry

Professor Sanjoy Chakraborty BIO 3620: Molecular and Cell Biology

50%

Ph.D., Molecular Biology Published a number of peer-reviewed research article in the field of Molecular Biology.

BIO 2311 Anatomy and Physiology I BIO 2312: Anatomy and Physiology II BIO 3601: Biochemistry

53

Professor Niloufar Haque BIO 3620: Molecular and Cell Biology Ph.D., Biochemistry/Molecular Biology

Published articles in top peer-reviewed journals in the field of Cell Biology. BIO 2311 Anatomy and Physiology I

BIO 2312: Anatomy and Physiology II BIO 3601: Biochemistry

50%

Extensive research experience in molecular biology, immunology, biochemistry and stem cell replacement therapy.

Reviewer in peer-reviewed journals.

Partnered with DANA Foundation Initiative for Brain Awareness Consultant in Molecular Neurobiology.

54

APPENDIX E: NEW RESOURCES

55

NEW RESOURCES

Expenditures Year 1

Academic Year2

Year 2

Academic Year†

Year 3

Academic Year†

Year 4

Academic Year†

Year 5

Academic Year†

Full Time Faculty Part Time Faculty

Full Time Staff Part Time Staff

0 0

0 0

0 0

0 0

0 0

0 0

0 0

0 0

0 0

0 0

Library (Includes Staffing) 1500 0 0 0 0

Equipment 0 0 0 0 0

Laboratories 0 0 8000 8000 16000

Supplies & Expenses (Other than Personal Services) 2000 2000 2000 2000 2000

Capital Expenditures 0 0 0 0 0

Other 0 0 0 0 0

Total all 3500 2000 10000 10000 18000

56

APPENDIX F: PROJECTED REVENUE

57

PROJECTED REVENUE

Projected Revenue Related to the Proposed Program

Revenues 1st Year

Academic Year 2nd Year

Academic Year 3rd Year

Academic Year 4th Year

Academic Year 5th Year

Academic Year Tuition Revenue 01. From Existing Sources 02. From New Sources 03. Total

$0 $134,579 $263,866 $387,383 $476,865 $176,625 $222,768 $270,686 $320,432 $372,059 $176,625 $357,347 $534,552 $707,815 $848,924

State Appropriation 04. From Existing Sources 05. From New Sources 06. Total

$0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0

Other Revenue 07. From Existing Sources 08. From New Sources 09. Total

$0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0

Grand Total 10. From Existing Sources 11. From New Sources**

TOTAL

$0 $134,579 $263,866 $387,383 $476,865

$176,625

$222,768 $270,686 $320,432 $372,059 $176,625 $357,347 $534,552 $707,815 $848,924

58

APPENDIX G: SUPPORTING MATERIALS FOR PROJECTED

REVENUE

59

SUPPORTING MATERIALS FOR PROJECTED REVENUE

The Five-Year Revenue Projections for Program SENIOR COLLEGE WORKSHEET

Year One Year Two Year Three Year Four Year Five Tuition & Fees: Existing Students are students currently enrolled in another program at your college, or students who would have enrolled in another program at your college, had the new program not been established.

Number of Majors (Enter # of EXISTING FULL TIME In State Students)

Tuition Income (Specify Rate per credit) calculates 2% increase per year Total Tuition

Student Fees (enter ANNUAL program fees other than standard CUNY fees) Total Fees Total Instate Tuition & Fees

Tuition & Fees:

Number of Majors (Enter # of EXISTING FULL TIME Out of State Students)


Student Fees (enter ANNUAL program fees other than standard CUNY fees) Total Fees Total Out of State Tuition & Fees

0 18 34 48 55

$5,130 $5,233 $5,337 $5,444 $5,553 $0 $94,187 $181,467 $261,312 $305,408

0 0 0 0 0 $0 $94,187 $181,467 $261,312 $305,408

0 0 0 0 0

$13,800 $14,076 $14,358 $14,645 $14,938 $0 $0 $0 $0 $0

0 0 0 0 0 $0 $0 $0 $0 $0

60

TOTAL EXISTING FULL TIME TUITION REVENUE

Tuition & Fees:

Number of Majors (Enter # of EXISTING PART-TIME In State Students)

Total Enrolled Credits (Enter Avg # credits per student per year-Fall+ Spring+Summer) i.e. 6 Fall, 6 Spring, 3 Summer=15



Tuition & Fees:

Number of Majors (Enter # of EXISTING PART-TIME Out of State Students)




$0 $94,187 $181,467 $261,312 $305,408

Year One Year Two Year Three Year Four Year Five

0 11 22 33 44

15 15 15 15 15

$240 $245 $250 $255 $260 $0 $40,392 $82,400 $126,072 $171,457

0 $0 $40,392 $82,400 $126,072 $171,457

0 0 0 0 0

$460 $469 $479 $488 $498 $0 $0 $0 $0 $0

0 $0 $0 $0 $0 $0

$0 $40,392 $82,400 $126,072 $171,457 TOTAL EXISTING PART TIME REVENUE 61

TOTAL EXISTING REVENUE (LINKS TO REVENUE SPREADSHEET ROW 5)

Year One Year Two Year Three Year Four Year Five $0 $134,579 $263,866 $387,383 $476,865

Tuition & Fees: New Students are students who would NOT have enrolled in another program at your college, had the new program not been established.

Number of Majors (Enter # of NEW FULL TIME In State Students)



Tuition & Fees:

Number of Majors (Enter # of NEW FULL TIME Out of State Students)



TOTAL NEW FULL TIME TUITION REVENUE

25 30 35 40 45

$5,130 $5,233 $5,337 $5,444 $5,553 $128,250 $156,978 $186,804 $217,760 $249,879

0 0 0 0 0 $128,250 $156,978 $186,804 $217,760 $249,879

0 0 0 0 0

$13,800 $14,076 $14,358 $14,645 $14,938 $0 $0 $0 $0 $0

0 0 0 0 0 $0 $0 $0 $0 $0

$128,250 $156,978 $186,804 $217,760 $249,879

62

Tuition & Fees:

Number of Majors (Enter # of NEW PART-TIME In State Students)




Tuition & Fees:

Number of Majors (Enter # of NEW PART-TIME Out of State Students)




TOTAL NEW PART TIME REVENUE


15 20 25 30 35

15 15 15 15 15

$215 $219 $224 $228 $233 $48,375 $65,790 $83,882 $102,672 $122,180

0 $48,375 $65,790 $83,882 $102,672 $122,180

0 0 0 0 0

$460 $469 $479 $488 $498 $0 $0 $0 $0 $0

0 0 0 0 0 $0 $0 $0 $0 $0

$48,375 $65,790 $83,882 $102,672 $122,180

63

TOTAL NEW REVENUE (LINKS TO REVENUE SPREADSHEET ROW 7)

State Revenue from EXISTING sources-identify sources

STATE BUDGET APPROPRIATIONS FROM EXISTING SOURCES -LINKS TO REVENUE SPREADSHEET ROW 9

State Revenue from NEW sources-identify sources

STATE BUDGET APPROPRIATIONS FROM NEW SOURCES -LINKS TO REVENUE SPREADSHEET ROW 11

FOR YEARS 2-5 INCLUDE CONTINUING RESOURCES FROM PREVIOUS YEARS

Other Revenue From Existing Sources (specify and explain)-LINKS TO REVENUE SPREADSHEET ROW 13)

Other Revenue New (specify and explain) (LINKS TO REVENUE SPREADSHEET ROW 15)

$176,625 $222,768 $270,686 $320,432 $372,059

Year One Year Two Year Three Year Four Year Five 0 0 0 0 0

$0 $0 $0 $0 $0

0 0 0 0 0

$0 $0 $0 $0 $0


0 0 0 0

0 0 0 0

64

APPENDIX H: FIVE YEAR FINANCIAL PROJECTION

65

0FIVE YEAR FINANCIAL PROJECTION

The Five-Year Financial Projections for Program

Direct Operating Expenses

Current Full Time Faculty Replacement Costs (list separately) Current Full Time Faculty Overload (include Summer) New Full Time Faculty Base Salary (list separetely) New Full Time Faculty Overload (include Summer) New Faculty Re-assigned Time (list seperately) Full Time Employee Fringe Benefits (33.0%)

Total (Links to Full-Time Faculty on Program Exp Worksheet)

Part Time Faculty Actual Salaries Part Time Faculty Actual Fringe Benefits (10%)

Total (Links to Part-Time Faculty Program Exp Worksheet)

Full Time Staff Base Salary (list separetely) Full Time Staff Fringe Benefits (33%)

Total (Links to Full-Time Staff on Program Exp Worksheet)

Year 1 Year 2 Year 3 Year 4 Year 5

0 0 0 0 0

0 0 0 0 0

0 0 0 0 0

0 0 0 0 0

0 0 0 0 0

0 0 0 0 0

66

(DO NOT INCLUDE NEW LIBRARY STAFF IN THIS SECTION) Part Time Staff Base Salary (list separately) Graduate Assistants Student Hourly Part Time Employee Fringe Benefits (10.0%)

Total (Links to Part-Time Staff on Program Exp Worksheet)

LIBRARY Library Resources Library Staff Full Time (List Separately) Full Time Staff Fringe Benefits (33%) Library Staff Part Time (List Separately) Part Time Employee Fringe Benefits (10.0%) TOTAL (Links to Library on Program Exp Worksheet)

EQUIPMENT Computer Hardware Office Furniture Other (Specify) Total (Links to Equipment on Program Exp Worksheet)

LABORATORIES Laboratory Equipment Other (list separately) - Supplies for BIO 3620 Labs TOTAL (Links to Laboratories on Program Exp Worksheet)


0 0 0 0 0

0 0 0 0 0

1500

0

0

0 0 0

0

0

0 0 0 1500 0 0 0 0

0 0 0 0 0

8000 8000 16000 0 0 8000 8000 16000

67

SUPPLIES AND EXPENSES (OTPS) Consultants and Honoraria Office Supplies Instructional Supplies Faculty Development Travel and Conferences Membership Fees Advertising and Promotion Accreditation Computer Software Computer License Fees Computer Repair and Maintenance Equipment Repair and Maintenance

New Total Supplies and OTPS Expenses (Links to Supplies on Program Exp Worksheet

CAPITAL EXPENDITURES Facility Renovations Classroom Equipment Other (list separately)

TOTAL (Links to Capital Expenditures on Program Exp Worksheet)

Other (list separately)

TOTAL (Links to Other on Program Exp Worksheet)


1000 1000 1000 1000 1000 1000 1000 1000 1000 1000

2000 2000 2000 2000 2000

0

0

0 0 0

0

0

0 0 0

68

APPENDIX I: ARTICULATION AGREEMENT

69

N E W Y O R K C I T Y COLLEGE OF TECHNOLOGY THE CITY UNIVERSITY OF NEW YORK 300 JAY STREET • BROOKLYN NEW YORK 11201-2983 Biological Sciences Department Room P305 • Phone (718) 260-5088

Proposal for B.S. Degree in Biomedical Informatics

Articulation Agreement with Borough of Manhattan Community College

ARTICULATION AGREEMENT FORM

College of Agreement Initiation: New York City College of Technology

A. SENDING AND RECEIVING INSTITUTIONS

Sending College: Borough of Manhattan Community College (BMCC) Department: Allied Health Sciences Department Program: HEALTH INFORMATION TECHNOLOGY Degree: Associate in Applied Science (AAS)

Receiving College: New York City College of Technology (NYCCT) Department: Biological Sciences Department Program: BIOMEDICAL INFORMATICS Degree: Bachelor of Science (BS)

B. ADMISSION REQUIREMENTS FOR SENIOR COLLEGE PROGRAM

A student must have a 2.5 average or better (or departmental approval otherwise) and have completed all requirements for the AAS Health Information Technology at BMCC to continue study at NYCCT.

Total transfer credit granted toward baccalaureate degree: 60 Total additional credits required by senior college to complete baccalaureate degree: 60

The Biological Sciences Department of New York City College of Technology (NYCCT) agrees to accept into the BS program in Biomedical Informatics students from Borough of Manhattan Community College (BMCC) who successfully complete an associates in applied science in Health Information Technology (HIT). Completion of the curriculum includes the attainment of at least a 2.5 overall grade-point average.

NYCCT and BMCC agree to offer the courses noted in the BS program in Biomedical Informatics (NYCCT) and the AAS HIT program (BMCC), as described in this agreement, and as outlined in each college’s course catalog. Each college agrees to notify the other if course numbers, content, or catalog descriptions change. Furthermore, the parties involved understand that any change in course number, content, or catalog description may require a modification to this agreement. C. COURSE-TO-COURSE EQUIVALENCIES AND TRANSFER CREDIT AWARDED

70

Students transferring from BMCC with an AAS in Health Information Technology shall enter the BS program in Biomedical Informatics at NYCCT as juniors. The following courses, totaling 60 credits, will be transferred to NYCCT via the course equivalencies indicated.

General Education (Liberal Arts, Core, Distribution) Course Equivalencies

Sending College Receiving College Equivalent Credits Granted

Course & Title CR Course & Title CR ENG 101 – English Composition I 3 ENG 1101 – English Composition 3 3 ENG 201 – English Composition II 3 ENG 1133 –Comm. for Tech. Students 3 3 PSY 100 – General Psychology 3 PSY 1101 – Introduction to

Psychology 3 3

SPE 100 – Fundamentals of Speech 3 Speech Comm. Elective (COMM Core)

3 3

HIT 204 – Health Statistics MAT 1372 – Stats. with Probability 3

11HIT 106 – Pathology of Diseases I 11 BIO 1101 – Biology I 4 HIT 103 – Medical Terminology I BIO 1201 – Biology II 4HIT 203 – Medical Terminology II Subtotal 23 Subtotal 23

Program-Specific Course Equivalencies

Sending College Receiving College Equivalent Credits Granted

Course & Title CR Course & Title CR BIO 425 – Anatomy & Physiology I 4 BIO 2311 – Anatomy & Physiology I 4 4 BIO 426 – Anatomy & Physiology II 4 BIO 2312 – Anatomy & Physiology II 4 4 HIT 208 – Pathology of Diseases II 3 BIO 3526 – Pathophysiology 3 3 CIS 106 – Intro to Health Info Technology

6 MED 2400 –Medical Informatics

Fundamentals 6 6CIS 206 – Intro to Health Info Systems HIT 331 – HIM Medical/Legal Applications HSA 3560 – Legal Aspects of

Healthcare HIT 108 – Health Data Info, Storage & Retrieval 3 MED 4229 – Healthcare Databases 3 3

HIT 332 – Quality Mgmt. & Improvement

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HSA 3510 – Health Services Mgmt. 3

14

HIT 423 – Management in the HIM Dept.

Elective Courses 11 MAT 150 – Introduction to Statistics HIT 207 – Coding & Classification Syst. I HIT 333 – Coding & Classification Syst. II HIT 421 – Coding & Classification Syst. III HIT 107 – Health Record Systems 3 HSA 4620 – Healthcare Information

Systems 3 3HIT 422 – Health Care Delivery Systems HIT 210 – Med Records Summer Clinical Practicum1 3

HIT 430: Professional Practice Experience1 4 Subtotal 44 Subtotal 37

TOTAL NUMBER OF CREDITS TRANSFERRED: 60

1 These two AAS practicum courses are not transferrable to the BS program, since they are neither Gen. Ed. courses nor do they fulfill any of the program-specific requirements of the Biomedical Informatics program.

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D. SENIOR COLLEGE UPPER DIVISION COURSES REMAINING FOR BS DEGREE

Students transferring to the BS program in Biomedical Informatics at NYCCT from the AS program in HIT at BMCC will be required to satisfactorily complete the following courses (totaling 60 credits) at NYCCT.

Gen Ed Courses to take at NYCCT

Code Course Credits ENG 3404 The Literature of Illness and Healthcare 3 PHIL 2203 Health Care Ethics 3 LAP Core Literature/Aesthetics/Philosophy Elective 3 BS Core Behavioral Science Elective 3 SS Core Social Science Elective 3 MAT 1475 Calculus I2 4 Subtotal 19

Program-Specific Courses to take at NYCCT

Code Course Credits BIO 3620 Molecular and Cell Biology 4 CST 1101 Problem Solving with Computer Programming 3 CST 1201 or CST 2403

Programming Fundamentals or Introductory C++ Programming Language 3

BIO 3350 Bioinformatics I 4 BIO 3352 Bioinformatics II 4 BIO 3354 Computational Genomics 3 BIO 3356 Molecular Modeling in Biology 3 MED 3910 Internship/Research in Biomedical Informatics 5 CST 1204 Database Systems Fundamentals 3 Subtotal 32

Electives (choose from the following courses, to total the number of credits specified)

Code Course Credits BIO 3601 Biochemistry

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BIO3524 Nutrition CHEM 1110 General Chemistry I CHEM 1210 General Chemistry II CHEM 2223 Organic Chemistry I CHEM 2323 Organic Chemistry II PHYS 1433 Physics 1.3 PHYS 1441 Physics 2.3 HSA 3510 Health Services Management II HSA 3630 Health Care Finance and Accounting Management CST 2309 Web Programming I CST 3503 C++ Programming Part II CST 3510 Computer Security MST 1204 Database Systems and Programming

2 Students without sufficient preparation for Calculus will have to take prerequisite courses before being admitted to MAT 1475, specifically MAT 1275 (College Algebra and Trigonometry) and MAT 1375 (Precalculus). The credits from these prerequisite courses shall not count towards the BS degree.

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MST 1205 Microcomputer Systems MST 2307 Local Area Networks MST 2405 Microcomputer Operating Systems CST 1215 Operating Systems Fundamentals CST 2307 Networking Fundamentals CST 2409 Web Programming II CST 3513 Object Oriented Programming in Java CST 3603 Object Oriented Programming MAT 1575 Calculus II MAT 2675 Calculus III MAT 2680 Differential Equations MAT 2440 Discrete Structures and Algorithms I MAT 2540 Discrete Structures and Algorithms II MAT 2580 Introduction to Linear Algebra MAT 3772 Stochastic Models Subtotal 9

TOTAL CREDITS TO BE TAKEN AT NYCCT: 60

E. ARTICULATION AGREEMENT FOLLOW-UP PROCEDURES

1. Procedures for reviewing, updating modifying or terminating agreement:

The Chair of the NYCCT Biological Sciences Department Dr. Walied Samarrai (or successor) and the Chair of BMCC Allied Health Sciences Department Dr. Everett Flannery (or successor) will review implementation of the agreement every two years to ensure that students are adequately informed of the program, and to identify issues requiring attention.

2. Procedures for evaluating the effectiveness of this agreement and tracking the number of students who transfer from BMCC to NYCCT under terms of this articulation agreement and their success:

After transfer into the NYCCT BS program in Biomedical Informatics, the performance of BMCC students will be tracked using the CUNY Institutional Research Data Base. The NYCCT Biological Sciences Department will inform BMCC about the academic progress of transfer students. Additionally, these students will be surveyed after graduation from NYCCT for information concerning students’ educational and professional experiences and accomplishments. NYCCT will share this information with BMCC.

The Biological Sciences Department at NYCCT will provide advisement to all BMCC students entering the BS Biomedical Informatics program.

3. Sending and Receiving College procedures for publicizing agreement, e.g., college catalogs, transfer advisors, Websites, etc.:

Notice of articulation will be placed in the respective catalogs, recruiting brochures, websites, and on the CUNY TIPPS website.

Respective transfer and academic advisers will be informed and provided with copies of this agreement.

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APPENDIX J: LETTER OF SUPPORT FROM DEAN KARL

BOTCHWAY

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APPENDIX K: EXTERNAL LETTERS OF SUPPORT

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APPENDIX L: EMPLOYMENT LISTINGS FOR BS

GRADUATES IN BIOMEDICAL INFORMATICS

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EMPLOYMENT LISTINGS FOR BS GRADUATES IN BIOMEDICAL INFORMATICS

This Appendix contains some sample listings for employment opportunities that successful graduates of the proposed program in Biomedical Informatics will be well-qualified to apply. These listings have been retrieved in February 2012 from widely-used job search websites. For reference, the full ads have also been included in this Appendix, after the listing summary below.

• BIOINFORMATICIAN, Mount Sinai School of Medicine (New York City), Division of Psychiatric Genomics in the Department of Psychiatry

o “We are looking for a talented, enthusiastic and self-motivated individual to join our team as an entry-level bioinformatics specialist and contribute to the novel research being done in the Division and at Mount Sinai. The bioinformatics specialist will be part of a team implementing and developing computational and statistical methods to analyze large amounts of human genetic data from structural variation to whole exome sequencing and relating this information to disease. Additionally, this individual will:

Assist researchers in implementation of tools for analysis of genome-wide data Setup and manage pipelines for handling and analyzing large datasets Manage disk usage and system resources Organize large datasets and associated files for distribution amongst group members and collaborators around the world

o Job Qualifications: BS in Computational Biology, Bioinformatics, Computer Science, Computer Engineering, Genetics or related field.”

• CLINICAL SOFTWARE ASSOCIATE, OmniComm Systems, Inc. (Monmouth Junction, NJ)

o “This entry level employee will be trained to design, configure, program, test and maintain clinical trial studies from initial build throughout the entire software project lifecycle.

o Skills needed: Some familiarity with application development and database development, along with relational database concepts. Demonstrated ability to understand and anticipate the needs of the customer and to provide solutions and recommendations. Excellent written, interpersonal and communication skills. Must possess the ability to clearly represent OmniComm and to project personnel both verbally and in writing.

o Qualifications needed: College degree with a major in either a technical field (such as Computer Science, Informatics, Applied Sciences) or a Scientific/Medical field (such as Biology, Computational Biology, Medical Technology, Pharmaceutical Sciences). Basic understanding of any of the following tools would be preferred: SQL and/or Microsoft SQL-Server, DHTML (HTML + Java Script), Microsoft IIS. Bachelor's degree in a technical or health-related field.”

• EHR INTEGRATION ANALYST, Nemours (Wilmington, DE), Children's Health Media Administration team

o “The Nemours Center for Children's Health Media/KidsHealth.org is seeking an individual to lead the medical encoding and clinical integration of the educational content created by the center under the brand KidsHealth. The center creates content around

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https://Media/KidsHealth.org

diagnosis, procedure, medication, discharge, chronic care & maintenance, which needs to be tied to the relevant medical code libraries.

o The ideal candidate would have a health informatics background, understanding of EHRs (Epic experience is preferable), understanding of the legislative landscape, a high degree of technical and analytic competency, and a passion for the role that excellent patient education can play in reforming the health care system.

o Responsibilities: Medical Encoding - Recruit, liaise, make assignments, supervise, manage payment/budgeting, and follow up with external medical encoding contractor(s) to ensure accurate assignment of codes to KidsHealth content from medical code libraries including but not limited to: ICD-9(Px), ICD-10(Px), HCSPCS/CPT, SNOMED, and NDC. This will also involve working with the IMO database to utilize the IMO to SNOMED crosswalk. Analysis - ensure proper functionality / optimal results of KidsHealth content within all Epic interfaces: diagnosis, procedure, medications, discharge instruction, in both Hyperspace (clinician) and MyNemours (patient). Liaise with Nemours Health Informatics – Assess usability and document how to use KidsHealth content from the clinical interface of Epic to help clinicians use our materials. Periodic uploads - work with Nemours Health Informatics for the required periodic imports to Epic of KidsHealth Discharge Instructions and KidsHealth LexiComp content links.

o Qualifications: Bachelor's Degree; prior experience in Health Informatics is preferred.”

• OUTPATIENT CODER/CLINICAL DATA SPECIALIST, Memorial Sloan-Kettering Cancer Center (New York, NY)

o “In this role, you will analyze medical records, extracting clinical, pathological, therapeutic and epidemiologic data in accordance with established ICD-9-CM and CPT-4 AMA coding principles and guidelines. The Coder ensures that data is optimally coded for research purposes, financial reimbursement, planning, statistics and regulatory reporting. Communicating directly with physicians to ensure that clinical documentation is coded timely, accurately, and in compliance with CMS guidelines and national coding initiatives.

o Qualifications: Bachelor Degree and/or RHIT/RHIA, Certified Coding Program highly preferred. Experience in outpatient coding with extensive knowledge of ICD-9CM coding, anatomy, physiology, and medical terminology. Experience in automated healthcare environment required. CCS, CCS-P, AAPC certifications preferred. Strong computer, verbal and written communication skills necessary, as well as analytical skills in identifying and assigning ICD-9-CM and CPT-4 coding per established guidelines.”

• RESEARCH ASSISTANT I, Children’s Hospital Boston (Boston, MA), DepartmentMedicine-Genetics

o “The Manton Center for Rare Disease Research seeks a Research Assistant I to provide computational and administrative support to Center investigators. Successful applicants will provide support with family linkage projects and interpretation of whole genome sequencing results. Previous computer programming experience is desirable but not necessary. Specifically, familiarity with Perl and/or statistical analysis software like S-plus or R is a plus. The successful candidate should be able to work independently and assist in collaborative projects with other Laboratories. Previous experience in any area of genetics and/or Bioinformatics research is desirable. A BS degree is required.”

• RESEARCH TECHNICIAN II, Massachusetts General Hospital (Boston, MA)

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o “The position requires strong analytical skills as well as familiarity with the mathematical techniques used in computational biology and a good problem-solving ability.

o Qualifications: A solid knowledge of the basics of graph theory, discrete mathematics, probability, statistics and algorithm design is a must. Good programming skills in at least one high-level programming language such as R, Python, or Matlab, are required. Experience working on problems in bioinformatics or computational biology is an asset. The ideal candidate will possess excellent organizational skills, pays close attention to detail, is willing to learn, is comfortable carrying out his/her work independently and enjoys working in a team environment. Minimum degree and field of knowledge: BS. 2 year commitment preferred.”

• SYSTEMS ANALYST II – INFORMATION TECHNOLOGY, Hackensack University Medical Center (Hackensack, NJ)

o “The Systems Analyst has knowledge of the functions and applications of information systems. The Systems Analyst is responsible for implementing and supporting clinical, financial, technical and administrative systems. The Systems Analyst need organizational and time management skills to handle deadlines and multiple projects.

o Education, Experience and Skills Required: Bachelor’s degree or Certification in applicable area of Information Technology or Healthcare.

o Education, Experience and Skills Preferred: Healthcare experience highly desirable. Epic Certification in clinical, financial or administrative applications desirable where appropriate.”

• COMPUTATIONAL BIOLOGIST, Van Andel Research Institute (Grand Rapids, MI), Laboratory of Neuroblastoma Translational Research

o “This position will be responsible for providing computational expertise to research programs that focuses on the storage, analysis, and distribution of digital (e.g. images, array files, proteomic spectra) clinical and biological data. Position involves data management: developing, maintaining, and supporting of associated biological software and databases; include leading data mining and data integration procedures. This position will also be responsible for assisting scientific staff by providing guidance in using bioinformatics in their research and preparing drafts and manuscripts to include abstracts and poster presentations.

o Functions: Handle computer based data management, analysis, and design and implement study-specific databases, programs, and software; may review, evaluate, and indirectly lead a computational work unit Develop, maintain, and support computational biology software Generate data queries based on validation checks or errors and omissions identified during data entry to resolve identified problems. Lead data mining, application prototyping, and data integration to support manipulation of clinical and biological data; includes developing and testing tools to mine and manage data Analyze clinical data using appropriate statistical tools. Ensure quality standard are met for patient data in clinical databases through data cleaning processes and data audits. Perform quality control audits to ensure accuracy, completeness, or proper usage of clinical systems and data.

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Prepare and/or review study reports, listings, tables, graphs and other presentations of study data. Assist scientific users in the application of bioinformatics (genomic expression array results and proteomic spectra) including assisting users with effective searching and reporting from genomic databases; includes providing bioinformatics input to experimental design and strategy, as needed Maintain the quality and integrity of the Institute’s data, proprietary information, and intellectual property including the Institute’s genomics sequence and expression databases Coordinate the work of the laboratory with that of Information Technology (IT) personnel Anticipate and keep abreast of new developments in bioinformatics and works to ensure the availability of state-of-the-art methods, resources, and data sources to support the user groups Perform all other duties as assigned

o Qualifications: Bachelor’s or Master’s degree or equivalent required in biology, mathematics, statistics, computer science, or other relevant scientific discipline. Knowledge and have experience using and/or developing computational tools and software for bioinformatics applications is preferred. Prefer progressive to complex laboratory experience in such functional areas: image analysis, DNA sequence analysis, and/or data integration. Direct experience with FDA regulations for healthcare such as CFR Part 11A is preferred; or the willingness to learn these regulations. Understanding of cellular biology or genetics is helpful. Should have demonstrated interest in computational biology and biomedical research and be able to work well as part of an interdisciplinary team of biologists, medical researchers, and computational biologists.

• INFORMATICS SPECIALIST/BIOINFORMATICIAN, Mayo Clinic (Rochester, MN) o Supports scientific projects under the supervision of an Informatics Lead or designated

senior level Informatics Specialists. Develops scripts or software applications to support data management, data extraction, data integration and data analysis as required.

o Should be knowledgeable in the handling and in the design of repository systems to contribute to the development of internal databases. Will have basic expertise in the informatics methods used to analyze data. Contributes to the design of analytical procedures and executes analytical procedures in the framework of a specific project. Contributes to the interpretation of data analysis and to writing reports.

o Basic Qualifications: Bachelor’s degree in domain-relevant sciences (biology, chemistry, mathematics, physics, and statistics or health sciences) or domain informatics (computational biology, computational chemistry, bioinformatics, clinical informatics, medical imaging, and medical informatics) required.

o Other Qualifications: Two years informatics experience and/or a master’s degree in domain-relevant sciences or domain informatics preferred. Good written and oral communication skills are required. Expertise in the use of informatics computing, scripting languages, and data management packages. Ability to prioritize, organizes, and delegates various tasks on projects. Frequently demonstrated initiative in administration, education (seminars, training), software development, technical reports.

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