2017 ieee international conference on bioinformatics and ... · pdf fileieee bibm 2017 program...

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2017 IEEE International Conference on

Bioinformatics and Biomedicine

Nov 13-16, 2017, Kansas City, MO, USA

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Sponsored by

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IEEE BIBM 2017

IEEE BIBM 2017 Program Schedule ................................................................................................................................ 4

Floor Plan ........................................................................................................................................................................... 9

Keynote Lectures ............................................................................................................................................................. 15

Invited Talks .................................................................................................................................................................... 18

Workshops ....................................................................................................................................................................... 21

Conference Paper Presentations ....................................................................................................................................... 35

Special Session on Medical Informatics and Engineering ............................................................................................... 46

Industry Session ............................................................................................................................................................... 47

Poster List ........................................................................................................................................................................ 47

Conference WiFi Access .................................................................................................................................................. 50

IEEE BIBM 2018 Call For Papers ................................................................................................................................... 51

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IEEE BIBM 2017 Program Schedule

Program

• November 13, 2017




Keynote Lecture: 60 minutes((about 45 minutes for talk and 15 minutes for Q and A)

Invited Talk: 40 minutes (about 30 minutes for talk and 10 minutes for Q and A)

Tutorial: 115 minutes (about 100 minutes for talk and 15 minutes for Q and A)

Main Conference Regular Paper: 20 minutes (about 15 minutes for talk and 5 minutes for Q and A)

Main Conference Short Paper: 15 minutes (about 12 minutes for talk and 3 minutes for Q and A)

Sunday, November 12

3:00– 8:00 pm

Registration

Washington Park Foyer

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Monday, Nov 13 (Workshops)

7:20am – 6:30pm Registration


10:20-10:40am

and 3:40-4:00pm

Coffee Break


12:00-1:30pm Lunch (On Own)

1:30-6:00pm Poster Session (Set Up)


8:00-12:30pm Workshops Workshop Chair Location

Workshop: The 2nd International Workshop on Semantics-Powered

Data Analytics (SEPDA 2017)

Zhe He, Cui Tao, Rui

Zhang, Jingshan Huang,

Jiang Bian

Brookside

Workshop: Data Analytics in Metagenomics/ Semantic Data

Analytics and Machine Learning in Bioinformatics and Medical

Informatics

Haiying Wang, Hui Wang

Rainer Roeche, Paul Walsh,

Huiru Zheng

Union Hill East

Workshop: International Workshop on Deep Learning in

Bioinformatics, Biomedicine, and Healthcare Informatics Jung Hun Oh, Mingon Kang Garden Parlor 918

Workshop: Workshop on Integrative Data Analysis in Systems

Biology (IDASB)

Zhongming Zhao, Rui

Jiang, Huiru Jane Zheng Crossroads

Workshop: 2017 Workshop on Health Informatics and Data Science Xiong Liu Signboard 1

Workshop: Biomedical and Health Informatics Illhoi Yoo

Washington Park 1

Workshop: 8th International Workshop on High Performance Bioinformatics

and Biomedicine (HiBB-2017)

Mario Cannataro Washington Park 2

Workshop: 1st International Workshop on Computational Methods

for the Immune System Function (CMISF 2017)

Francesco Pappalardo and

Marzio Pennisi Washington Park 3

Workshop: International Workshop on Biological Network Analysis

and Integrative Graph-Based Approaches

Mingon Kang, Dongchul

Kim, Young-Rae Cho Signboard 2

Workshop: The International Workshop on High Throughput

Computing in Bioinformatics and Biomedicine using Open Science

Grid

Juan Cui, David Swanson Penn Valley

Workshop: Biological Ontologies and knowledge bases workshop Jiajie Peng, Jin Chen Roanoke

Workshop: 1st International Workshop on Affective Computing in

Biomedicine and Healthcare

Prof. Huiru (Jane) Zheng,

Dr. Raymond Bond Garden Parlor 818

1:30-6:00pm Workshops/Tutorials Workshop Chair Location

Workshop: The 2nd International Workshop on Semantics-Powered

Data Analytics (SEPDA 2017)

Zhe He, Cui Tao, Rui

Zhang, Jingshan Huang,

Jiang Bian

Brookside

Workshop: Data Analytics in Metagenomics/ Semantic Data

Analytics and Machine Learning in Bioinformatics and Medical

Informatics

Haiying Wang, Hui Wang

Rainer Roeche, Paul Walsh,

Huiru Zheng

Union Hill East

Workshop: International Workshop on Deep Learning in

Bioinformatics, Biomedicine, and Healthcare Informatics Jung Hun Oh, Mingon Kang Garden Parlor 918

Workshop: Workshop on Integrative Data Analysis in Systems

Biology (IDASB)

Zhongming Zhao, Rui

Jiang, Huiru Jane Zheng Crossroads

Workshop: 2017 Workshop on Health Informatics and Data Science Xiong Liu Signboard 1

Workshop: Biomedical and Health Informatics Illhoi Yoo

Washington Park 1

Workshop: Network Based Data Integration and Analysis: Towards

Precision Medicine Pietro Hiram Guzzi Washington Park 2

Workshop: Computer Based Processes and Algorithms for

Biomedicine and Life Quality Improvement P. Veltri Garden Parlor 818

Workshop: The 4th International Workshop on High Performance

Computing on Bioinformatics

Che-Lun (Allen) Hung,

Huiru Zheng Washington Park 3

Workshop: Reproducibility and Robustness in Biological Data

Analysis and Integration Kathryn Cooper Signboard 2

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Workshop: Applied Informatics in pharmacology and

pharmacogenomics/Knowledge Discovery in Translational

Biomedical Informatics/Translational Bioinformatics in Precision

Medicine (TBPM)

Dhundy R Bastola, Kritika

Karri, Feichen Shen, Yuji

Zhang, Lixia Yao,

Hongfang Liu

Roanoke

Tuesday, November 14

8:00am-6:00pm

Registration


8:45-9:00am

Welcome and Opening Session Conference and PC Chairs: Xiaohua Hu, Chi-Ren Shyu, Yana Bromberg, Jean Gao, Yang Gong, Dmitry Korkin

Washington Park Ballroom

9:00-10:00am

Keynote Lecture 1 (Chair: Xaohua Hu )

“Biological Big Data Analytics: Challenges and Algorithms”

Prof. Sanguthevar Rajasekaran, University of Connecticut, USA


10:00-10:20am Coffee Break


10:20-12:30pm Sessions Session Chair Location

Session1: Genomics Nabavi, Sheida Brookside

Session2: Biological Networks Pietro Hiram Guzzi Washington Park 1

Session3: Medical Informatics Chen Fang Crossroads

Session4: Biomedical Text Mining Mario Cannataro Washington Park 3

10:20-7pm Poster Session Setup and Display


12:30-2:00pm Lunch provided by Conference Benton’ Prime, Sign Board, Union Hill and Brookside


Session5: Translational Bioinformatics, Cheminformatics and

pharmacogenomics I Mingon Kang Brookside

Session6: Structure, Function and Evolution Amarda Shehu Washington Park 1

Session7: Semantics and Ontology Rohithkumar Nagulapati Crossroads

Session8: Medical Informatics Moumita Bhattacharya Washington Park 3

Special Session on Medical Informatics and Engineering Hansu Cai Garden Parlor 918

Industry Session Nan Alan Zhao Union Hill East

Workshop Biomedical and Health Informatics Illhoi, Yoo Garden Parlor 818

3:40-4:00pm Coffee Break

Foyer


Session 9: Structure, Function and Evolution Xue, Bin Brookside

Session 10: Next-Gen Sequencing Nhat Tran Washington Park 1

Session 11: Biomedical Text Mining II Tony Hu Crossroads

Session 12: Microarray, SNPs and Haplotype Analysis, GWAS,

Personalized Genomics Wang, Junwen

Washington Park 3

Special Session on Medical Informatics and Engineering

Hansu Cai

Garden Parlor 918

http://www.cis.drexel.edu/faculty/thu/

https://muii.missouri.edu/person/chi-ren-shyu/

http://dbm.rutgers.edu/pages/Yana_Bromberg.html

http://crystal.uta.edu/~gao/

https://sbmi.uth.edu/faculty-and-staff/yang-gong.htm

https://www.wpi.edu/people/faculty/dkorkin

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Industry Session Nan Alan Zhao Union Hill East

Workshop Biomedical and Health Informatics Illhoi Yoo Garden Parlor 818

Wednesday, Nov 15

8:00am-6:00pm

Registration Washington Park Foyer

9:00-10:00am

Keynote Lecture 2 (Chair: Jean Gao)

Adventures with large biomedical datasets: diseases, medical records, environment and genetics

Prof. Andrey Rzhetsky, University of Chicago, USA




10:20am -12:30pm Sessions Session Chair Location

Session 13: Computational Modeling and Data Integration I Sean West Brookside

Session 14: AI and Machine Learning Methods in Biomedical

Informatics Dimitri Perrin

Washington Park

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Session15: Biomedical Intelligence, Clinical Data Analysis Sheets, Lincoln R Crossroads

Session16: Biomedical Signal/Image Analysis I Ersoy, Ilker Washington Park

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12:30-2:00pm Lunch provided by Conference

Benton’ Prime, Sign Board, Union Hill and Brookside

2:00-3:00pm

Keynote Lecture 3 (Chair: Chi-Ren Shyu) Towards Automated Deep Learning Model Construction and Its Applications in Computational Chemical Biology

Prof. Jun (Luke) Huan, University of Kansas, USA


Poster Session Washington Park Foyer

3:00 – 3:20 pm Coffee Break

Washington Park Foyer 3:20-4:00pm Sessions Session Chair Location

Invited Talks

Invited Talk 1: Differential Privay Preserving Deep Learning in

Healthcare, Prof Xintao Wu, University of Arkansas , USA Dmitry Korkin Brookside

Invited Talk 2:ChIP-Seq Data Completion and Transcription

Factors Binding Analyses, Prof. De-Shuang Huang, Tongji

University, China

Chi-Ren Shyu Washington Park

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Invited Talk 3:An Energy Landscape View of Protein

Structure, Dynamics, and (Dys)Function, Prof. Amarda

Shehu, George Mason University, USA

Yana Bromberg Crossroads

Invited Talk 4:Radiomics – beyond imaging for personalized

and precision medicine, Prof. Paolo Soda, Università Campus

Bio-Medico di, Italy

Gong, Yang Washington Park

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Informatics II Tran, QuocNam Brookside

Session 18: Biomedical Signal/Image Analysis II Thomas Fevens Signboard

Session 19: Clinical Decision Support and Informatics Mary Yang Crossroads

Session 20: Healthcare Informatics Gong, Yang Union Hill East

7:00-9:00pm

Banquet (Ticket required)

1. Best Paper Award (Conf Chair, PC Chairs, TCCLS Chair)

2. Best Student Paper Award (Conf Chair, PC Chairs, TCCLS Chair)


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Thursday, Nov 16

8:00-10:00am

Registration


9:00-10:00am

Keynote Lecture 4 (Chair: Gong, Yang)

Going beyond Patterns: Deep Understanding of Biology with Machine Learning

Prof. Predrag Radivojac, Indiana University Bloomington, USA Washington Park Ballroom



10:00 - 10:20 am Poster Display


10:20am-12:30pm Sessions Session Chair Location

Session 21: Computational Modeling and Data Integration II Wang, Haiying Brookside


Informatics III Dingcheng Li Washington Park 1

Session 23: Healthcare Informatics II Mathews, Sherin M Crossroads

Session 24: Biological Data Mining, Visualization, High

Performance Computing

BHATTACHARYYA

MAHUA Washington Park 3

8:00-12:30noon Workshop: Machine Learning and Big Data Research for

Disease Classification and Complex Phenotyping Jinbo Bi Roanoke

8:00-12:30noon Workshop: Data mining from genomic variants and its

application to genome-wide analysis 2017 Taesung Park Penn Valley

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Floor Plan

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Keynote Lectures

Keynote 1: Biological Big Data Analytics: Challenges and Algorithms

Speaker: Prof. Sanguthevar Rajasekaran, University of Connecticut, USA

Abstract:

We live in an era of big data. Voluminous datasets are generated and have to be processed in every area of science

and engineering. This is especially true in biology. Efficient techniques are needed to process these data. In particular,

we need tools to extract useful information from massive data sets. Society at large can benefit immensely from

advances in this arena. For example, information extracted from biological data can result in gene identification,

diagnosis for diseases, drug design, etc. Market-data information can be used for custom-designed catalogues for

customers, supermarket shelving, and so on. Weather prediction and protecting the environment from pollution are

possible with the analysis of atmospheric data.

In this talk we present some challenges existing in processing biological big data. We also provide an overview of

some basic techniques. In particular, we will summarize various data processing and reduction techniques.

Short Bio:

Sanguthevar Rajasekaran received his M.E. degree in Automation from the Indian Institute of Science (Bangalore)

in 1983, and his Ph.D. degree in Computer Science from Harvard University in 1988. Currently he is the Board of

Trustees Distinguished Professor, UTC Chair Professor of Computer Science and Engineering, and the Director of

Booth Engineering Center for Advanced Technologies (BECAT) at the University of Connecticut. Before joining

UConn, he has served as a faculty member in the CISE Department of the University of Florida and in the CIS

Department of the University of Pennsylvania. During 2000-2002 he was the Chief Scientist for Arcot Systems. His

research interests include Big Data, Bioinformatics, Algorithms, Data Mining, Randomized Computing, and HPC.

He has published over 350 research articles in journals and conferences. He has co-authored two texts on algorithms

and co-edited six books on algorithms and related topics. His research works have been supported by grants from

such agencies as NSF, NIH, DARPA, and DHS (totaling $9M as the PI and an additional $9M as a co-PI). He is a

Fellow of the Institute of Electrical and Electronics Engineers (IEEE) and the American Association for the

Advancement of Science (AAAS). He is also an elected member of the Connecticut Academy of Science and

Engineering.

Keynote 2: Adventures with large biomedical datasets: diseases, medical records, environment and genetics

Speaker: Prof. Andrey Rzhetsky, University of Chicago, USA

Abstract:

I will attempt to cover several interrelated analysis topics, spending more time on parts that resonate with the

audience. First, I will introduce our recent study analyzing phenotypic data harvested from over 150 million unique

patients. Curiously, these non-genetic large-scale data can be used for genetic inferences. We discovered that

complex diseases are associated with unique sets of rare Mendelian variants, referred to as the “Mendelian code.”

We found that the genetic loci indicated by this code were enriched for common risk alleles. Moreover, we used

probabilistic modeling to demonstrate for the first time that deleterious Mendelian variants likely contribute to

complex disease risk in a non-additive fashion.

The second topic that I hope to cover is analysis of apparent clusters of neurodevelopmental disorders. Disease

clusters are defined as geographically compact areas where a particular disease, such as a cancer, shows a significantly

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increased rate. It is presently unclear how common are such clusters for neurodevelopmental maladies, such as autism

spectrum disorders (ASD) and intellectual disability (ID). As in the first story, examining data for one third of the

whole US population, we demonstrated that (1) ASD and ID are manifesting strong clustering across US counties;

(2) counties with high ASD rates also appear to have high ID rates, and (3) the spatial variation of both phenotypes

appears to be driven by environment, and, by a lesser extent, by economic incentives at the state level.

The third topic is about using electronic medical record data to 1) estimate the heritability and familial environmental

patterns of diseases, and 2) infer the genetic and environmental correlations between disease pairs from a set of

complex diseases. I am particularly interested in inferring objective classifications// of diseases (based on a formal

optimization criterion), separately from environmental and genetic factors

Short Bio:

Andrey Rzhetsky is an Edna K. Papazian Professor of Medicine and Human Genetics, at the University of Chicago.

He is also a Pritzker Scholar, and a Senior Fellow of both the Computation Institute, and the Institute for Genomics

and Systems Biology at the University of Chicago.

His research is focused on computational analysis of complex human phenotypes in context of changes and

perturbations of underlying molecular networks. The input data for these studies is supplied by large-scale mining of

free text, computation over clinical records, and high-throughput systems biology experiments

Keynote 3: Towards Automated Deep Learning Model Construction and Its Applications in Computational

Chemical Biology

Speaker: Prof. Jun (Luke) Huan, University of Kansas, USA

Abstract:

In recent years, research in Artificial Neural Networks (ANNs) has resurged, now under the Deep-Learning umbrella,

and grown extremely popular due to major breakthroughs in methodological and computing capabilities. Deep-

Learning methods are part of representation-learning algorithms that attempt to extract and organize discriminative

information from the data. Recently reported success of DL techniques in crowd-sourced chemical biology data

analysis and predictive toxicology competitions has showcased these methods as powerful tools for drug-discovery

and toxicology research. Nevertheless, reported applications of Deep Learning techniques for modeling complex

bioactivity data for small molecules remain still limited.

In this talk I will present our recent work on optimizing feed-forward Deep Neural Nets (DNNs) hyper-parameters

and performance evaluation of these methods as compared to shallow methods. In our study 48 DNNs, 24 Random

Forest, 20 SVM and 6 Naïve Bayes arbitrary but reasonably selected configurations were compared employing 7

diverse bioactivity datasets assembled from ChEMBL repository combined with circular fingerprints as molecular

descriptors. Our results demonstrate that DNNs are powerful modeling techniques for modeling complex bioactivity

data. I will then talk about a project towards a collaborative environment where we support the automated

construction, optimization, profiling, sharing, running, and reusing deep (and shallow) machine learning models.

Short Bio:

Dr. Jun (Luke) Huan is the Charles E. & Mary Jane Spahr Professor in the Department of Electrical Engineering and

Computer Science at the University of Kansas. He directs the Data Science and Computational Life Sciences

Laboratory at KU Information and Telecommunication Technology Center (ITTC).

Dr. Huan works on data science, machine learning, data mining, big data, and interdisciplinary topics including

bioinformatics and health informatics. He has published more than 120 peer-reviewed papers in leading conferences

and journals and has graduated more than ten graduate students including seven PhDs. Dr. Huan serves the editorial

board of several international journals including the Springer Journal of Big Data, Elsevier Journal of Big Data

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Research, and the International Journal of Data Mining and Bioinformatics. He regularly serves the program

committee of top-tier international conferences on machine learning, data mining, big data, and bioinformatics.

Dr. Huan's research is recognized internationally. He was a recipient of the National Science Foundation Faculty

Early Career Development Award in 2009. His group won the Best Student Paper Award at the IEEE International

Conference on Data Mining in 2011 and the Best Paper Award (runner-up) at the ACM International Conference on

Information and Knowledge Management in 2009. His work appeared at mass media including Science Daily, R&D

magazine, and EurekAlert (sponsored by AAAS). Dr. Huan's research was supported by NSF, NIH, DoD, and the

University of Kansas.

Starting January 2016, Dr. Huan serves as a Program Director in NSF at its Intelligent and Information Division in

the Computer and Information Science and Engineering Directorate.

Keynote 4: Going beyond Patterns: Deep Understanding of Biology with Machine Learning

Speaker: Prof. Predrag Radivojac, Indiana University Bloomington, USA

Abstract: A major goal in computational biology is the development algorithms, analysis techniques, and tools towards deep

mechanistic understanding of life at a molecular level. In the process, computational biology must take advantage of

the new developments in artificial intelligence and machine learning, and then move beyond pattern analysis to

provide testable hypotheses for experimental scientists. This talk will focus on our contributions to this process and

the relevant related work. We will first discuss the development of machine learning techniques for partially

observable domains such as molecular biology; in particular, methods for accurate estimation of frequency of

occurrence of hard-to-measure and rare events. We will then show how these methods play key roles in inferring

protein function and the phenotypic effect of coding sequence variants, with an emphasis on understanding the

molecular mechanisms of human genetic disease. We will assess the value of these methods in a wet lab where we

tested the molecular mechanisms behind selected de novo mutations in a cohort of individuals with

neurodevelopmental disorders. We finally discuss implications for genome interpretation.

Short Bio:

Predrag Radivojac is a Professor of Computer Science at Indiana University Bloomington. Prof. Radivojac received

his Bachelor's and Master's degrees in Electrical Engineering from the University of Novi Sad and University of

Belgrade, Serbia. His Ph.D. degree is in Computer Science from Temple University (2003) under the direction of

Prof. Zoran Obradovic and co-direction of Prof. Keith Dunker. In 2004 he held a post-doctoral position in Keith

Dunker's lab at Indiana University School of Medicine, after which he joined Indiana University Bloomington. Prof.

Radivojac's research is in the areas of computational biology and machine learning with specific interests in protein

function, MS/MS proteomics, genome interpretation, and precision health. He received a National Science

Foundation (NSF) CAREER Award in 2007 and is an honorary member of the Institute for Advanced Study at

Technical University of Munich. Prof. Radivojac's projects have been supported by NSF and National Institutes of

Health (NIH). He is currently an Editorial Board member for the journal Bioinformatics, Associate Editor for PLoS

Computational Biology, and serves on the Board of Directors of the International Society for Computational Biology

(ISCB)..

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Invited Talks Invited Talk 1: Differential Privay Preserving Deep Learning in Healthcare

Speaker: Prof Xintao Wu, University of Arkansas , USA

Abstract:

The remarkable development of deep learning in healthcare domain presents obvious privacy issues, when deep neural

networks are built on users’ personal and highly sensitive data, e.g., clinical records, user profiles, and biomedical images.

In this talk, we concentrate on recent research on differential privacy preserving deep learning. Differential privacy

ensures that the adversary cannot infer any information about any particular record with high confidence (controlled by

a privacy budget) from the released learning models. In the first part of this talk, we introduce the concept of differential

privacy and present several mechanisms, including Laplace mechanism, exponential mechanism, input perturbation, and

functional perturbation, that have been developed to enforce differential privacy in data mining and machine learning

models. In the second part of this talk, we discuss how to apply and adapt those mechanism to preserve differential

privacy in deep learning models. In particular, we discuss how to achieve differential privacy by injecting noise into input

data, gradient descents of parameters, or loss functions of deep learning models. Finally we present challenges and

findings when applying differential privacy preserving deep learning models for human behavior prediction and

classification tasks in a health social network.

Short Bio:

Dr. Xintao Wu is the professor and the Charles D. Morgan/Acxiom Endowed Graduate Research Chair in Database and

leads Social Awareness and Intelligent Learning (SAIL) Lab in Computer Science and Computer Engineering

Department at the University of Arkansas. He was a faculty member in College of Computing and Informatics at the

University of North Carolina at Charlotte from 2001 to 2014. Dr. Wu's major research interests include data mining,

privacy and security, fairness aware learning, and big data analysis. His recent research work has been to develop 1)

privacy preserving techniques for mining tabular data, social network data, healthcare data, and GWAS data; 2) spectral

analysis based fraud detection techniques in social networks; and 3) causal network based discrimination detection and

prevention in training data and prediction models. Dr. Wu has published over 100 scholarly papers. He and his students

received several awards including a PAKDD'09 Best Student Paper Runner-up Award, WISE'12 Challenge Runner-up

Award, PAKDD'13 Best Application Paper Award, and BIBM'13 Best Paper Award. Dr. Wu has served on editorial

boards of several international journals and frequently served on program committees of top international conferences,

including ACM KDD, CIKM, IEEE ICDM, BIBM, SIAM SDM, PKDD, and PAKDD. Dr. Wu is a recipient of NSF

CAREER Award (2006), Excellence in Undergraduate Teaching Award (2005), and Outstanding Faculty Research

Award (2009) from College of Computing and Informatics at UNC Charlotte, and Outstanding Researcher Award from

Computer Science and Computer Engineering Department at University of Arkansas.

Invited Talk 2: ChIP-Seq Data Completion and Transcription Factors Binding Analyses

Speaker: Prof. De-Shuang Huang, Tongji University, China

Abstract:

Transcription factors (TFs), as the key regulatory elements of gene transcription, can activate or suppress the transcription

by binding to specific sets of DNA sequences. In the past, the introduction of ChIP-seq sequencing technologies provides

immense opportunities for precise categorization of TF binding sites. In this talk, we will introduce several novel

computational models for integrative analysis of the accumulated ChIP-seq data. Firstly, due to cost, time or sample

material availability, it is not always possible for researchers to obtain ChIP-seq data for every TF in every sample of

interest, which considerably limits the power of integrative studies. To tackle this problem, we propose Local Sensitive

Unified Embedding (LSUE) for imputing new ChIP-seq datasets. Secondly, we construct gene regulatory networks in 13

human tissues by integrating large-scale transcription factor (TF)-gene regulations with gene and protein expression data.

By comparing these regulatory networks, it was found that many tissue-specific regulations that are important for tissue

identity. In particular, the tissue-specific TFs are found to regulate more genes than those expressed in multiple tissues,

and the processes regulated by these tissue-specific TFs are closely related to tissue functions. Therefore, recognizing

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tissue specific regulatory networks can help better understand the molecular mechanisms underlying diseases and identify

new disease genes.

Short Bio:

De-Shuang Huang is Chaired Professor in Department of Computer Science and Director of Institute of Machine Learning

and Systems Biology at Tongji University, China. He received his M.S. and Ph.D. in electronic engineering from National

Defense University of Science and Technology and Xidian University, China, in 1989 and 1993, respectively. He was

the Recipient of “Hundred Talents Program of Chinese Academy of Sciences” (2000). He was also visiting professors at

the George Washington University, Washington DC, USA (2003), Queen’s University of Belfast, UK (2006) and Inha

University, Korea (2007, 2008 & 2009). Currently, he is the visiting professor of the Liverpool John-Moore University,

UK. His main research interest includes neural networks, pattern recognition and bioinformatics.

De-Shuang Huang is currently the Fellow of the International Association of Pattern Recognition (IAPR Fellow), the

Board Member of the International Neural Network Society (INNS) Governors, a Senior Member of the IEEE and the

Senior Member of INNS, Bioinformatics and Bioengineering Technical Committee Member of IEEE CIS, Neural

Networks Technical Committee Member of IEEE CIS, the member of the INNS, Co-Chair of the Big Data Analytics

section within INNS, and associated editors of several main-stream international journals such as Neural Networks, etc.

He founded the International Conference on Intelligent Computing (ICIC) in 2005. ICIC has since been successfully

held annually with him serving as General or Steering Committee Chair. He also served as the 2015 International Joint

Conference on Neural Networks (IJCNN 2015) General Chair, July 12-17, 2015, Killarney, Ireland, the 2014 11th

IEEE Computational Intelligence in Bioinformatics and Computational Biology Conference (IEEE-CIBCBC) Program

Committee Chair, May 21-24, 2014, Honolulu, USA, and the 2014 IEEE World Congress on Computational

Intelligence-International Joint Conference on Neural Networks, Technical Committee Co-Chair, July 6-11, 2014,

Beijing, China as well as The 2013 International Joint Conference on Neural Networks, Asia Liaison, August 4-9,

2013, Dallas, TX, USA.

He has published over 360 papers in international journals, international conferences proceedings, and book chapters.

Particularly, he has published over 160 SCI indexed papers. Also, he published three monographs (in Chinese), one of

which, entitled with “Systematic Theory of Neural Networks for Pattern Recognition”, won the Second-Class Prize of

the 8th Excellent High Technology Books of China in 1997.

Invited Talk 3: An Energy Landscape View of Protein Structure, Dynamics, and (Dys)Function

Speaker: Prof. Amarda Shehu, George Mason University, USA.

Abstract:

The energy landscape underscores the inherent nature of proteins as dynamic systems interconverting between structures

with varying energies. Recently, our laboratory has developed a computational framework that feasibly reconstructs

energy landscapes of any forms of a protein of interest, thus allowing investigating in silico the impact of pathogenic

mutations on equilibrium structure and dynamics. The framework operates under the umbrella of stochastic optimization

and leverages experimentally-known, stable and semi-stable structural states of a protein’s variants to reconstruct the

energy landscape of any variant of interest. The availability of landscapes of wildtype and diseased variants of a protein

opens the way for data mining techniques to harness quantitative information embedded in landscapes. We share findings

from a recent line of research in our laboratory that automatically extracts the hierarchical organization and structure of

a molecular energy landscape and summarizes a landscape with geometric attributes. As we demonstrate on an enzyme

central to human biology and health, mining landscapes allows categorizing variants and summarizing mechanisms via

which mutations alter dynamics and function. We share results on oncogenic and syndrome-causing variants of the human

Ras enzyme. These results signal an exciting stage where machines can compute and mine landscapes to autonomously

learn how mutations impact function and even elucidate the role of specific structural states and transitions of a protein

variant in biological activities in the cell.

Short Bio:

Dr. Amarda Shehu is an Associate Professor in the Department of Computer Science at George Mason University and is

also affiliated with the School of Systems Biology and the Department of Bioengineering. Shehu received her B.S. in

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Computer Science and Mathematics from Clarkson University in Potsdam, NY in 2002 and her Ph.D. in Computer

Science from Rice University in Houston, TX in 2008, where she was an NIH fellow of the Nanobiology Training

Program of the Gulf Coast Consortia. Shehu’s research contributions are in computational structural biology, biophysics,

and bioinformatics with a focus on issues concerning the relationship between sequence, structure, dynamics, and

function in biological molecules. Her research is supported by various NSF programs, including Intelligent Information

Systems, Computing Core Foundations, and Software Infrastructure. Shehu is also the recipient of an NSF CAREER

award and two Jeffress Memorial Trust Awards. Shehu is an associate editor of IEEE Transactions in Computational

Biology and Bioinformatics. She has served as program committee chair and general chair of the IEEE BIBM and ACM

BCB conferences and is routinely a guest editor of special collections and issues in journals, such as PLoS Computational

Biology, IEEE Transactions in Computational Biology and Bioinformatics, BMC Structural Biology, and J

Computational Biology.

Invited Talk 4: Radiomics – beyond imaging for personalized and precision medicine

Speaker:

Prof. Paolo Soda, Università Campus Bio-Medico di, Italy

Abstract:

Radiomics refers to the computation, analysis and selection of advanced quantitative imaging features with high

throughput from standard-of-care medical images acquired using, for instance, CT, PET or MRI. Indeed, the increasing

adoption of electronic patient records as well as the diffused use of PACS have made available heterogeneous patient

data, spanning different spatial and temporal scales, modalities, and functionalities. Radiomics is also evolving into

radiogenomics that looks for correlation between cancer imaging features and gene expression. On the basis of such

image features, medical and biological data, radiomics and radiogenomics are currently directed towards the development

of personalized and precision medicine models that aim to provide valuable diagnostic, prognostic or predictive

information.

Short Bio:

Prof. Paolo Soda, PhD, is an Associate Professor in Computer Science at the Department of Engineering, University

Campus Bio-Medico di Roma (UCBM), Italy. His research interests include pattern recognition, machine learning, big

data analytics, and data mining applied to data, signal, 2D and 3D image and video processing and analysis. Practical

applications of the research activities have impacted on the biomedical applications, with reference to computer-aided

diagnosis and decision support systems. Prof. Paolo Soda has received six external grants from both government funding

agencies and industry, totalizing over 500 thousand euros in external funding. He has published over 80 refereed papers

in international journals and conference proceedings, being also co-author of two international patents. Since June 2017

Paolo serves as chair of the IEEE Technical Committee on Computational Life Sciences (http://tccls.computer.org/).

Since 2012, he has also served as associate editor of the proceedings of the annual international conference of the IEEE

Engineering in Medicine & Biology Society, and since the same year he has been a member of the Steering Committee

of the International Symposium on Computer-Based Medical Systems (CBMS). He was general co-chair of the 25th and

29th CBMS editions in 2012 and 2016, respectively. In the last few years, Paolo Soda has also served as program and

special tracks co-chair. From 2009 to 2012 he co-organized at CBMS special tracks on knowledge discovery and decision

systems in biomedicine, and in 2012 he co-organized a contest on bioimage classification at the 21st International

Conference on Pattern Recognition. He also currently serves as member of the program committee in several conferences.

He was guest editor of Pattern Recognition (vol. 47(7), 2014) and Artificial Intelligence in Medicine (vol. 50(1), 2010).

Prof. Paolo Soda received his Master’s diploma and PhD in biomedical engineering from UCBM in 2004 and 2008,

respectively, co-founding with his supervisor, Prof. Giulio Iannello, the Unit of Computer Systems and Bioinformatics.

He continued as a postdoctoral researcher in 2009 at the Department of Engineering, UCBM, and as an assistant professor

from 2010 to 2014 at the Department of Medicine, UCBM. In 2013 and 2015 he held a digital imaging class at the

Technical Medical Superior School of Locarno, Switzerland; in 2014 he held a machine learning class at the faculty of

Computer Science, Henan University, China, and in 2009 and 2012 he got European training grants to carry out scientific

and teaching activities on machine learning and computer vision at the Polytech'Nice, Université de Nice-Sophia

Antipolis, France, and at the Eindhoven University of Technology, The Netherlands.

21

Workshops

Workshop on Biomedical and Health Informatics (BHI)

One & Half days: 11/13 and 11/14 (afternoon); Room: Washington Park 1 Workshop Chairs: Illhoi Yoo

Time Title Presenter/Author

9:15am Welcome (Chair)

9:20 Geometrical mapping of diseases with calculated similarity

measure

Yuichi Yaguchi, Mai Omura, and

Takashi Okumura

9:45 Towards the design of a Secure and Compliant Framework for

OpenEMR

Subrata Acharya, Alexander Mak, and

Yuehan Yin

10:00-10:20 Coffee Break

10:20

The Recommender System for a Cloud-Based Electronic

Medical Record System for Regional Clinics and Health

Centers in China

Sunhao Hu, Lu Lu, Xinbin Jin, Yinyin

Jiang, Haowen Zheng, Qiufan Xu,

Fangfang Cai, Yu Meng, and

Changjiang Zhang

10:35 Identifying Articles Relevant to Drug-Drug Interaction:

Addressing Class Imbalance

Gongbo Zhang, Moumita Bhattacharya,

Heng-Yi Wu, Pengyuan Li, Lang Li, and

Hagit Shatkay

11:00 Biomedical Analysis of HbA1c based on Microfluidic Chips Wenpeng Guo

11:15-1:30 Lunch (on your own)

1:30 Early Illness Recognition in Older Adults Using Transfer

Learning

Rayan Gargees, James Keller, and

Mihail Popescu

1:55

Ultra-Short-Term Analysis of Heart Rate Variability for Real-

time Acute Pain Monitoring with Wearable Electronics

Mingzhe Jiang, Riitta Mieronkoski,

Amir M. Rahmani, Nora Hagelberg,

Sanna Salanterä, and Pasi Liljeberg

2:20 Fraise: A Framework for Predicting Peak Postprandial Blood

Glucose using Personalized Data-Driven Modeling Eric Rozier

2:35 Evaluation of Relational and NoSQL Approaches for Patient

Cohort Identification from Heterogeneous Data Sources

Ningzhou Zeng, GQ Zhang, Xiaojin Li,

and Licong Cui

3:00 Automated Adjustment of Crowdsourced Calorie Estimations

for Accurate Food Image Logging

Patrick McAllister, Anne Moorhead,

Raymond Bond, and Huiru (Jane) Zheng

3:15 Automated Clinical Diagnosis: The Role of Content in Various

Sections of a Clinical Document

Vivek Datla, Sadid A. Hasan, Ashequl

Qadir, Kathy Lee, Yuan Ling, Joey Liu,

and Oladimeji Farri


4:00 Segmentation of Tumor and Edema Based on K-mean

clustering and Hierarchical Centroid Shape Descriptor

Ravi Shanker, Rahul Singh, and Mahua

Bhattacharya

4:25 Classification of breast tumors as benign and malignant using

textural feature descriptor

Mukta Sharma, Rahul Singh, and Mahua

Bhattacharya

4:40 Mammographic Image Segmentation by Marker Controlled

Watershed Algorithm

Arnab Chattaraj, Arpita Das, and Mahua

Bhattacharya

Continued in the 11/14 afternoon

22

Workshop on Biomedical and Health Informatics (BHI)

One & Half days: 11/13 and 11/14 (afternoon); Room: Garden Parlor 818 Workshop Chairs: Illhoi Yoo


1:50 Functional Protein Networks Underlying the Comorbidity of

Gout and Hyperuricemia Guang Zheng

2:15 Supervised Approach to Rank Predicted Links using

Interestingness Measures

Murali Krishna Pusala, Ryan G Benton,

Vijay V Raghavan, and Raju

Gottumukkala

2:40 Descriptor Based Protein Structure Representation using

Triangular Spatial Relationships in 3-D

Sumi Singh, Vijay Raghavan, and Wu

Xu

2:55 A Statistics and UMLS-based Tool for Assisted Semantic

Annotation of Brazilian Clinical Documents

Lucas Emanuel Silva e Oliveira,

Caroline Pilatti Gebeluca, Adalniza

Moura Pucca da Silva, Sadid Al Hasan,

Oladimeji Farri, and Claudia Maria

Cabral Moro

3:20

Deep Convolutional Triplet Network for Quantitative Medical

Image Analysis with Comparative Case Study of Gamma Image

Classification

Phawis Thammasorn, Landon Wootton,

Eric Ford, Wanpracha A.

Chaovalitwonse, and Matthew Nyflot


4:00 Designing a Low-Cost Adaptable and Personalized Remote

Patient Monitoring System

Eva Lee, Yuanbo Wang, Robert Davis,

and Brent Egan

4:30 Inpatient Bed Management to Improve Care Delivery Eva Lee, Andriy Shapoval, and Zixing

Wang

5:00 A Weighted Similarity Measure Approach to Predict Intensive

Care Unit Transfers

Aditya patel, Izzatbir Singh, Landon

Brand, and Roheet Rao

5:25 A Semantic Knowledge-Base Approach to Drug-Drug

Interaction Discovery

Ignacio Tripodi, Kevin Cohen, and

Lawrence Hunter

5:40 Closing Remarks

International Workshop on Deep Learning in Bioinformatics, Biomedicine, and Healthcare

Informatics (DLB2H 2017) Workshop Chairs: Jung Hun Oh and Mingon Kang


9:00 – 9:20 Improving the Generalization of Disease Stage Classification with

Deep CNN for Glioma Histopathological Images

Asami Yonekura, Hiroharu Kawanaka, V. B.

Surya Prasath, Bruce J. Aronow, and

Haruhiko Takase

9:20 – 09:40 Assessing impacts of data volume and data set balance in using deep

learning approach to human activity recognition

Haipeng Chen, Fuhai Xiong, Dihong Wu,

Lingxiang Zheng, Ao Peng, Xuemin Hong,

Biyu Tang, Hai Lu, Haibin Shi, and Huiru

Zheng

09:40 – 10:00 Deep learning for skin lesion segmentation Rashika Mishra and Ovidiu Daescu

10:00 – 10:20 Coffee Break

10:20 – 10:40 Deep vs. Shallow Learning-based Filters of MSMS Spectra in Support

of Protein Search Engines

Majdi Maabreh, Basheer Qolomany, James

Springstead, Izzat Alsmadi, and Ajay Gupta

10:40 – 11:00 Deep Gramulator: Improving Precision in the Classification of

Personal Health-Experience Tweets with Deep Learning

Ricardo Calix, Ravish Gupta, Matrika Gupta,

and Keyuan Jiang

11:00 – 11:20 Dorsal Hand Vein Recognition Based On Convolutional Neural

Networks

Haipeng Wan, Hong Song, Lei Chen, and

Jian Yang

11:20 – 2:00 Lunch

2:00 – 2:20 Mitochondria Segmentation in Electron Microscopy Volumes using

Deep Convolutional Neural Network

Ismail Oztel, Gozde Yolcu, Ilker Ersoy,

Tommi White, and Filiz Bunyak

23

2:20 – 2:40 Learning Influential Genes on Cancer Gene Expression Data with

Stacked Denoising Autoencoders

Vítor Teixeira, Rui Camacho, and Pedro

Gabriel Ferreira

2:40 – 3:00 Prediction of Enhancer RNA Activity Levels from ChIP-seq-derived

Histone Modification Combinatorial Codes

Nawanol Theera-Ampornpunt and Somali

Chaterji

3:00 – 3:20 Reconstruction of high read-depth signals from low-depth whole

genome sequencing data using deep learning

Yao-zhong Zhang, Seiya Imoto, Satoru

Miyano, and Rui Yamaguchi

3:20 – 3:40 R-PathCluster: Identifying Cancer Subtype of Glioblastoma

Multiforme Using Pathway-Based Restricted Boltzmann Machine

Tejaswini Mallavarapu, Youngsoon Kim,

Jung Hun Oh, and Mingon Kang


4:00– 4:20 Interpretable Convolutional Neural Networks for Effective Translation

Initiation Site Prediction

Jasper Zuallaert, Mijung Kim, Yvan Saeys,

and Wesley De Neve

4:20 – 4:40 Towards Alzheimer's Disease Classification through Transfer

Learning Marcia Hon and Naimul Mefraz Khan

4:40 – 5:00 Extracting Retinal Vascular Networks Using Deep Learning

Architecture Yasmin Kassim and Kannappan Palaniappan

Closing Remarks

The 2nd International Workshop on Semantics-Powered Data Analytics (SEPDA 2017) Workshop Chairs: Zhe He, Jiang Bian, Cui Tao, Rui Zhang, and Jingshan Huang


8:00 – 8:05 Opening Remarks Zhe He

8:05– 8:40 Keynote: Dr. Cui Tao (University of Texas Health Science Center at Houston) Cui Tao

8:40 – 8:50 Short Break

8:50– 10:10 Session 1: Natural Language Processing (Session Chair: Zhe He)

Automatic Methods to Extract New York Heart Association Classification from

Clinical Notes Rui Zhang

Towards practical temporal relation extraction from clinical notes: an analysis of direct

temporal relations Hee-Jin Lee

Extraction of protein-protein interactions using natural language processing based

pattern matching Jinfeng Zhang

Evaluating Automatic Methods to Extract Patients’ Supplement Use from Clinical

Reports Rui Zhang

10:10– 10:30 Coffee Break

10:30 – 11:50 Session 2: Ontology and Knowledgebase (Session Chair: Jingshan Huang)

Designing an Ontology for Emotion-driven Visual Representations Muhammad F. Amith

OC-2-KB: A software pipeline to build an evidence-based obesity and cancer

knowledge base

Juan Antonio Lossio-

Ventura

Auditing the Assignments of Top-Level Semantic Types in the UMLS Semantic

Network to UMLS Concepts Zhe He

Auditing Subtype Inconsistencies among Gene Ontology Concepts Rashmie Abeysingh

11:50 – 2:00 Lunch Break

2:00 – 3:20 Session 3: Ontology-Based Data Analytics (Session Chair: Rui Zhang)

A pilot study of mining association between psychiatric stressors and symptoms in

tweets Jingcheng Du

Exploratory Textual Analysis of Consumer Health Languages for People Who are

D/deaf and Hard of Hearing Zhe He

Ontology-guided Semantic Data Integration to Support Integrative Data Analysis: A

Case Study of Cancer Survival Hansi Zhang

MeSH term-based semantic analysis of microRNA regulation on glucocorticoid

resistance in pediatric acute lymphoblastic leukemia Jingshan Huang


3:50 – 5:10 Session 4: Deep Learning and Data Mining (Session Chair: Jiang Bian)

Computer-aided Diagnosis of Four Common Cutaneous Diseases Using Deep Learning

Algorithm Xinyuan Zhang

An Exploration of Semantic Relations in Neural Word Embeddings Using Extrinsic

Knowledge Zhe He

Chemical-induced Disease Extraction via Convolutional Neural Networks Haodi Li

24

Query-constraint-based Association Rule Mining from Diverse Clinical Datasets in the

National Sleep Research Resource

Rashmie Abeysingh

5:10 – 5:15 Closing Remarks

Network Based Data Integration and Analysis: Towards Precision Medicine

WorkshopChairs: Pietro Hiram Guzzi


2:30- 2:45 Opening Pietro Hiram Guzzi

2:45- 3:00

Gionata Fragomeni, Giuseppe Tradigo, Lina Teresa Gaudio, and Pierangelo Veltri,Development of a DSS for cardiovascular prevention and rehabilitation

Pierangelo Veltri

3:00- 3:15

Monica Jha, Hazel N Manners, Pietro Hiram Guzzi, Pierangelo Veltri, and Swarup Roy, Network Based Algorithms for Module Extraction from RNASeq Data: A Quantitative Assessment.

Swarup Roy

3:15- 3:30

Jincai Yang, Fuli Zhang, Xingpeng Jiang, Xiaohua Hu, and Xianjun Shen, Classify and identify the risky Loci of type 2 diabetes with computational method

Jincai Yang

Coffee Break

4:00- 4:15

Hazel N Manners, Ahed Elmsallati, Pietro Hiram Guzzi, Swarup Roy, and Jugal Kalita,Performing Local Network Alignment by Ensembling Global Aligners

Pietro Hiram Guzzi

4:15- 5:30

Jincai Yang, Chunjie Guo, Xingpeng Jiang, Xiaohua Hu, and Xianjun Shen, Systematic Characterization and Prediction of Tumor-associated MiRNAs in Mouse

Jincai Yang

5:30- 6 45

Xiangyi Meng, Quan Zou, Alfonso Rodrıguez-Paton, and Xiangxiang zeng, Iteratively collective prediction of disease-gene associations through the incomplete network

Xiangyi Meng

6: 45- 7 00 Closing Remarks

1st International Workshop on Computational Methods for the Immune System Function (CMISF

2017) (Morning , room 8) WorkshopChairs: Francesco Pappalardo, Pedro Reche, Marzio Pennisi


09:00-09:20 A mathematical model to study breast cancer growth Marzio Pennisi

09:20-09:40 Optimization and analisys of vaccination shedules using Simulated

Annealing and Agent Based Models Giulia Russo

09:40-10:00 Introducing scale factor adjustments on agent-based simulations of the

immune system Pedro Reche


10:20-10:40 Integrated biomedical data analysis utilizing various types of data for

biomarkers identification Nicholas West

10:40-11:00 In-Silico Analysis of the “Memory Anti-Naive” Effect in Anti-Viral

Cross-Reactive Responses Dario Ghersi

11:00-11:20 Tumor Escape: A Mathematical Model Santo Motta

11:20-11:40 Symetries and Asymetries of the Immune System: a categorification

approach Jean-Francois Mascari

11:40-12:00 MCVdb: a database for knowledge discovery in Merkel cell

polyomavirus with applications in T cell immunology and vaccinology Guanglan Zhang

25

12:00-12:20 A simplified mathematical-computational model of the immune

response to the yellow fever vaccine Carla Bonin

12:20-12:40 On the use of Gillespie stochastic simulation algorithm in a model of

the human immune system response to the Yellow Fever vaccine Carla Bonin

12:40-13:00 Complementing single-cell RNA-seq using bulk transcriptional

profiles Winston Haynes

13:00-13:10 Closing Remarks

Joint workshop on Knowledge Discovery in Translational Biomedical Informatics, Applied

Informatics in pharmacology and pharmacogenomics, and Translational Bioinformatics in Precision

Medicine Chairs: Feichen Shen, Yuji Zhang, Lixia Yao, Hongfang Liu, Dhundy Bastola, Kritika Karri, Abolfazl Doostparast Torshizi, Kai Wang


2:25-2:40 A Hybrid Protein-Protein Interaction Triple Extraction Method for

Biomedical Literature Zhehuan Zhao

2:40-2:55 Pharmacogenomic-Based Medication Risk Assessment in People with

Polypharmacy Jiazhen Liu

2:55-3:10 The Design and Implementation of the Elderly Healthcare Information

Mining Platform Rongzhen Yan

3:10-3:25 Exploring Social Contextual Influences on Healthy Eating using Big

Data Analytics Vijaya Kumari Yeruva

3:25-3:40

Medical Concept Intersection between Outside Medical Records and

Consultant Notes: A Case Study in Transferred Cardiovascular

Patients

Feichen Shen


4:00-4:15 Mining FDA resources to compute population-specific frequencies of

adverse drug reactions Aleksandar Poleksic

4:15-4:30 Drug-Drug Interaction Relation Extraction with Deep Convolutional

Neural Networks Ika Novita Dewi

4:30-4:45 Introducing Pharmacogenomic Decision Support for Medication Risk

Assessment in People with Polypharmacy Jiazhen Liu

4:45-5:00 CuHerbDB- for Pharmacogenomics and Study of Phytochemicals in

Culinary and Medicinal Herbs Dhundy K. Bastola

5:00-5:15 A Deep Learning based Scoring System for Prioritizing Susceptibility

Variants for Mental Disorders A.Khan

Reproducibility and Robustness in Biological Data Analysis and Integration (RRoBIn 2017) Workshop Chairs: Kathryn Cooper, Sanjukta Bhowmick, Hesham Ali


1:45 Introduction to RRoBIn Hesham Ali

2:05

Contributed Paper: "Digital Reproducibility of Computational Genomic

Workflows"

Sehrish Kanwal

2:30 Contributed Paper: "On the Reproducibility of Biological Image

Workflows by Annotating Computational Results Automatically" Frank Taubert

2:55

Contributed Paper: “Comparison of location-scale and matrix

factorization batch effect removal methods on gene expression datasets”

Emilie Renard

3:30 Coffee Break

3:50

Contributed Paper: "Classifying Protein Crystallization Trial Images

Using Subordinate Color Channel"

Truong Tran

4:15 Contributed Paper: “The Ontology Reference Model for Coordinating

Drug-target Interactions Data” Qiong Cheng

26

4:50 Panel: Interdisciplinary Views on Reproducibility and Robustness

Closing Remarks

Kathryn Cooper, University of

Nebraska at Omaha

Feichen, Mayo Clinic

TBD

2017 Workshop on Health Informatics and Data Science (HI-DS) Workshop Chair: Xiong Liu


9:00-9:30

Prediction of Short Term Adverse Events Occurrence in NB-UVB

Phototherapy Treatments using Data mining

Sharifa Mohamed, Bingquan Huang, and

Mohand-Tahar Kechadi

9:30-10:00

Automated Classification of Adverse Events in Pharmacovigilance

Shantanu Dev, Shinan Zhang, Joseph Voyles,

and Anand Rao

10:00-10:20

Coffee Break

10:20-10:50

Drug Accessibility and Availability Tool: Case of Rwanda

Danny Habamwabo and Bertin Akim

Mpagazi

10:50-11:20

Phenotyping Physicians with Frequent Malpractice Claims

Joseph Finkelstein and Sinan Zhu

11:20-11:50

Patient Empowerment in Online Support Group for

Temporomandibular Disorder

Karen Lin and Joseph Finkelstein

11:50-12:20

Action Recognition Based on Depth Image Sequence

Liangcan Liao, Guitao Cao, and Wenming

Cao

12:20-1:30

Lunch (on your own)

1:30-2:00

The Impact of Risk Stratification on Care Coordination

Sheets Lincoln, Lyttle Kayson, Popejoy Lori

L., Petroski Gregory F., Joshua Geltman,

Mosa Abu S. M., Katie Wilkinson, and

Parker Jerry C.

2:00-2:30

Environment Effects on the Usage of Pediatric Hospitals in Shanghai,

a Retrospective Study from 2013 to 2014

Guang-jun Yu, Wen-bin Cui, Ting Lu, Jian-

lei Gu, Jian-ping Jiang, Yang Wang, and Hui

Lu

2:30-3:00

Health-Related Rumour Detection On Twitter

Rosa Sicilia, Stella Lo Giudice, Yulong Pei,

Mykola Pechenizkiy, and Paolo Soda

3:00-3:30

Improving Validity of Cause of Death on Death Certificates

Janani Venugopalan, Hang Wu, Li Qu, and

May Wang

3:30-4:00

Coffee Break

4:00-4:30

A Novel Secure Text Messaging Solution

Subrata Acharya and Matthew McDonald

4:30-5:00

Towards the design of a comprehensive Data De-Identification

Solution

Subrata Acharya and Anoli Patel

5:00-5:30

Parallel Algorithm for indexing large DNA Sequences Using

MapReduce on Hadoop

Venu Madhav Kuthadi, Freeson Kaniwa, and

Otlhapile Dinakenyane

5:30-6:00

EpCom: A Parallel Community Detection Approach for Epidemic

Diffusion over Social Networks

Heng Zhang, Libo Zhang, Da Cheng, Yanjun

Wu, and Chen Zhao

Closing Remarks

27

Workshop Computer based processes and algorithms for biomedicine and life quality improvement WorkshopChair: Pierangelo Veltri


2:00– 2:10 Workshop Welcome and Introduction Pierangelo Veltri

2:10-2:30 S10201 A Crowdsourcing Method for Correcting Sequencing Errors

for the Third-generation Sequencing Data

Yu Geng, Zhongmeng Zhao, Zhaofang Du,

Yixuan Wang, Tian Zheng, Siyu He,

Xuanping Zhang, and Jiayin Wang

2:30– 2:50 S10203 mEEG:A system for EEG management and analysis"

domenico mirarchi, Patrizia Vizza, Pietro

Cinaglia, Giuseppe Tradigo, and Pierangelo

Veltri,

2:50– 3:10 S10207 Deep Learning-based Facial Expression Recognition for

Monitoring Neurological Disorders

Gozde Yolcu, Ismail Oztel, Serap Kazan,

Cemil Oz, Kannappan Palaniappan, Teresa

Lever, and Filiz Bunyak,

3:10-3:30 S10204 Development and Testing of an Application Based on

Coronary Artery Diseases (CAD)

Gionata Fragomeni, Lina Teresa Gaudio,

Michela Destito, Pierangelo Veltri, Salvatore

De Rosa, and Ciro Indolfi,


4:00-4:20 S10208 Using Gait Parameters to Recognize Various Stages of

Parkinson Disease

Elham Rastegari, Vivien Marmelat,

Lotfollah Najjar, Dhundy K. Bastola, and

Hesham Ali

4:20-4:40 S10205 On a recent algorithm for Multiple Instance Learning.

Preliminary applications in image classification"

Annabella Astorino, Antonio Fuduli,

Pierangelo Veltri, and Eugenio Vocaturo

4:40-5:00 S10206 eIMES 3D Mobile: a mobile application for diagnostic

procedures

Pasquale Iaquinta, M Iusi, Luciano

Caroprese, Salvatore Turano, Salvatore

Palazzo, Francesco Dattola, Ivana Pellegrino,

Giuseppe Tradigo, Giuseppe Cascini,

Pierangelo Veltri, and Ester Zumpano,

5:00– 5:10 Closing Remarks

Biological Ontologies and Knowledge bases

WorkshopChairs: Jiajie Peng, Jin Chen


9:00-9:20 Identifying Diseases-related Metabolites Based on Network Lingling Zhao, Tianyi Zhao, Yang Hu,

and Liang Cheng

9:20-9:40 Effective Norm Emergence in Cell Systems Under Limited

Communication Xiaotian Hao, Jianye Hao, and Li Wang

9:40-10:00 Towards the Classification of Cancer Subtypes by Using Cascade Deep Forest Model in Gene Expression Data

Yang Guo


10:20-10:40 Learning Reference-enriched Approach towards Large scale

Active Ontology Alignment and Integration Qiong Cheng, Oleg Ursu, Tudor Oprea,

and Stephan Schurer

10:40-11:00 Higher-order partial least squares for predicting gene

expression levels from chromatin states Shiquan Sun, Xifang Sun, and Yan

Zheng

11:00-11:20 Measuring phenotype-phenotype similarity through the

interactome Jiajie Peng, Weiwei Hui, and Xuequn

Shang

11:20-11:40 Automatic Infection Detection based on Electronic Medical

Records Huaixiao Tou, Lu Yao, and Zhongyu Wei

11:40-12:00 A framework for analyzing DNA methylation data from Illumina

Infinium HumanMethylation450 BeadChip Zhenxing Wang and Yadong Wang

Closing Remarks

28

10th International Workshop on Biological Network Analysis and

Integrative Graph-Based Approaches (IWBNA 2017) WorkshopChairs: Mingon Kang, Dongchul Kim, and Young-Rae Cho


9:00-9:20 A Global Biomolecular Network Alignment Method Based on

Network Flow Model

Jiang Xie, Jiaxin Li, Jiao Wang, Qing Nie,

and Wu Zhang

9:20-9:40 ParaMODA: Improving Motif-Centric Subgraph Pattern Search

in PPI Networks Somadina Mbadiwe and Wooyoung Kim

9:40-10:00 Correlation Networks: Biologically Driven Relationships from

Gene Expression Data Grogan Huff and Kathryn Cooper


10:20- 10:40 Classifying Gene Coexpression Networks Using State Subnetworks Bassam Qormosh, Eihab El Radie and

Saeed Salem

10:40-11:00 Mining Quasi Frequent Coexpression Subnetworks Eihab El Radie and

Saeed Salem

11:00-11:20

Analysis of Structural Measurements in Correlation Networks Built

from Gene Expression Data across Different Tissue Types

in Mus Musculus

Qianran Li and Kathryn Cooper

11:20- 11:40 Graph Regularized Robust Non-negative Matrix Factorization for

Clustering and Selecting Differentially Expressed Genes

Na Yu, Ying-Lian Gao, Jin-Xing Liu,

Chun-Hou Zheng, Juan Wang and

Ming-Juan Wu

11:40-12:00 Feature Selection and Clustering via Robust Graph-Laplacian PCA

Based on Capped L1-Norm

Ming-Juan Wu, Ying-Lian Gao,

Jin-Xing Liu, Chun-Mei Feng and

Xiang-Zhen Kong

12:00-12:20 Mining Cross-Ontology Weighted Association Rules between GO

and HPO

Joseph Huang, Collin Rapp and

Young-Rae Cho Closing Remarks

The International Workshop on High Throughput Computing in Bioinformatics and Biomedicine

using Open Science Grid Workshop Co-chairs: Juan Cui and David Swanson

ROOM 11


9:00-9:10 Welcome David Swanson

9:10- 9:25 OSG-KINC: High-Throughput Gene Co-Expression Network Construction Using the

Open Science Grid William Poehlman

9:25-9:40 MiRDR-OSG: MicroRNA Dynamic Regulation Analysis utilizing Open Science Grid Jiang Shu

9:40-9:55 NanoAsPipe: A transcriptome analysis and alternative splicing detection pipeline for

MinION long-read RNA-seq. Kan Liu


10:20-10:35 A Simulation Model of Glucose-Insulin Metabolism and Implementation on OSG Aditya Immaneni

10:30- 10:50 When technology meets technology: Retrained ‘Inception V3’ classifier for the NGS

based pathogen detection Rohita Sinha

29

11:00-11:40 Keynote talk Don Krieger

11:40-11:55 Shared High Value Research Resources: The CamCAN Human Lifespan Neuroimaging

Dataset Processed on the Open Science Grid Don Krieger

11:55-12:10 Using High-Throughput Computing for Dynamic Simulation of Bipedal Walking Mohammadhossein

Saadatzi


Machine Learning and Big Data Analysis for Disease Classification Session Chairs: Jinbo Bi, Guoqing Chao, Jin Lu

Time Title

9:00-10:40 Session 1 (15 minutes for each talk, including Q and A)

Session Chair: Dr. Jin Lu

8:50-9:00 Opening remarks

9:00-9:15 Predicting Sentinel Node Status in Melanoma from a Real-World EHR Dataset

9:15-9:30 Metabolic Pathway and Graph Identification of New Potential Drug Targets for Plasmodium Falciparum

9:30-9:45 Compressive Sampling for Phenotype Classification

9:45:10:00 Markov Blanket: Efficient Strategy for Feature Subset Selection Method for High Dimensional Microarray

Cancer Datasets


10:20-11:20 Session 2 (15 minutes for each talk, including Q and A)

Session Chair: Dr. Jin Lu

10:20-10:35 Predicting MCI Progression with Individual Metabolic Network Based on Longitudinal FDG-PET

10:35-10:50 A novel depression detection method based on pervasive EEG and EEG splitting criterion

10:50-11:05 Predicting ADHD using 3D Convolutional Neural Networks and fMRI Data

11:05-11:20 Brain tumor extraction with Deep Belief Network

11:20 Closing

The 4th International Workshop on High Performance Computing on Bioinformatics WorkshopChairs: Che-Lun (Allen) Hung, Huiru Zheng, Chuan Yi Tang, Chun-Yuan Lin


2:40-3:00 Accelerating Scoring Computation of Smith-Waterman Algorithm

with Mixed Word Length Kazuki Yasui and Fumihiko Ino

3:00-3:20 Deep Learning–based MSMS Spectra Reduction in Support of

Running Multiple Protein Search Engines on Cloud

Majdi Maabreh, Basheer Qolomany, Izzat

Alsmadi, and Ajay Gupta

3:20-3:40 Robust Graph Regularized Sparse Orthogonal Nonnegative Matrix

Factorization for Identifying Differentially Expressed Genes

Ling-Yun Dai, Jin-Xing Liu, Chun-Hou

Zheng, Jun-Liang Shang, Chun-Mei Feng,

and Ya-Xuan Wang

Coffee Break

4:00-4:20 High-Throughput Structural Modeling of the HIV Transmission

Bottleneck Scott Morton, Julie Phillips, and Joshua

Phillips

4:20-4:40 Data Provenance Management for Bioinformatics Workflows using

NoSQL Database Systems in a Cloud Computing Environment

Fernanda Hondo Tedesque, Polyane

Wercelens, Klayton Castro, Waldeyr da

Silva, Ingrid Santana, Aleteia Araujo, Maria

Emília Walter, Sergio Lifschitz, and

Maristela Holanda

4:40-5:00 Scalable Data Structure to Compress Next-Generation Sequencing

Files and its Application to Compressive Genomics Sandino Vargas Perez and Fahad Saeed

5:00-5:20 Bioinformatics tools with Deep Learning based on GPU Che-Lun Hung and Chuan Yi Tang Closing Remarks

30

8th International Workshop on High Performance Bioinformatics and Biomedicine (HiBB-2017) Workshop Chair: Mario Cannataro


9:00 – 9:20 B229 - Detecting Complex Indels with Wide Length-Spectrum from

the Third Generation Sequencing Data

Xuanping Zhang, Hengwei Chen, Rong

Zhang, Jingwen Pei, Yixuan Wang,

Zhongmeng Zhao, Yi Huang, and Jiayin

Wang

9:20-9:40 S19204 - A Parallel Algorithm for Mining Maximal Frequent

Subgraphs Eihab El Radie and Saeed Salem

9:40 – 10:00 B563 - An Iterative Algorithm for de novo Optical Map Assembly Menglu Li, Siu-Ming Yiu, Ting-Fung Chan,

and Ernest T. Lam


10:20-10:40 S19202 - Deep Learning to Extract Laboratory Mouse Ultrasonic

Vocalizations from Scalograms Adam Smith and Drew Kristensen

10:40-11:00 B575 - Higher Order Finite Difference Modeling of Cardiac

Propagation Riasat Khan and Kwong Ng

11:00-11:20 S19201 - Sentiment Analysis and Affective Computing for depression

monitoring

Chiara Zucco, Barbara Calabrese, and Mario

Cannataro

11:20-11:40 S19203 - A software pipeline for multiple microarray data analysis Mario Cannataro and Giuseppe Agapito

11:40-12:00 B585 - Detecting Chromosomal Structural Variation using Jaccard

Distance and Parallel Architecture

Hamidreza Mohebbi, Amir Vajdi, Nurith

Haspel, and Dan Simovici

12:00-12:10 Closing Remarks of HiBB-2017 Workshop

12:30-2:00 Lunch Break

1st International Workshop on Affective Computing in Biomedicine and Healthcare Workshop Chairs: Huiru(Jane) Zheng, Raymond Bond, Paul Walsh Room 9, 13 Nov 2017


9:00-9:20

Participatory Design-based Requirements Elicitation Involving

People Living with Dementia - Towards a Home-based Platform to

Monitor Emotional Wellbeing

Maurice Mulvenna, Huiru (Jane) Zheng,

Raymond Bond, Patrick McAllister, Haiying

Wang, and Rubén Riestra

9:20-9:40 Approach to Semi-Automatic Labeling of Video Sequences for

Affective Computing

Thilo Böhm, Felix Engel, Danilo Bzdock,

Frank Schneider, and Matthias Hemmje

9:40-10:00 Stability study of the optimal channel selection for emotion

classification from EEG

Hong Peng, Yongzong Wang, Bin Hu, Jinlong

Chao, and Majoe Dennis


10:20-10:40 Continuous Affect Prediction Using Eye Gaze and Speech Jonny O' Dwyer, Ronan Flynn, and Niall

Murray

10:40-11:00 Tracking and Evaluation of Pupil Dilation via Facial Point Marker

Analysis

Anas Samara, Leo Galway, Raymond Bond,

and Hui Wang

11:00-11:20 The role of reproducibility in Affective Computing

Felix Engel, Alphonsus Keary, Kevin

Berwind, Marco Xaver Bornschlegl, and

Matthias Hemmje

11:20-11:40 Detecting Demeanour for Connected Health with Machine Learning Michael Healy and Paul Walsh

11:40-12:00 Speech Pause Time: A Potential Biomarker for Depression Detection Zhenyu Liu, Huanyu Kang, Lei Feng, and Lan

Zhang

12:00-12:20

Does Tang Poetry Affect Human Emotional State? A Pilot Study by

EEG

Panpan Wang, Yazhou Zhang, Xiang Li,

Yuexian Hou, and Dawei Song



31

Workshop on Semantic Data Analytics and Machine learning in Bioinformatics and Medical

Informatics Session Chair: Dr. Haiying Wang


9:00-9:05 Opening Remarks

9:05–9:40 Invited talk: Biological Network Comparison

Prof. Pietro Hiram Guzzi

9:40–10:00 The Ontology Reference Model for Visual Selectivity Analysis in

Drug-target Interactions

Qiong Cheng, Felix Lopez, Celia Duran,

Christopher Camarillo, Tudor Oprea, and

Stephan Schurer

10:00– 10:20 Coffee Break

10:20-12:20 Session I (approximately 20 mins for each talk)

A Novel Hybrid Subset-Learning Method for Predicting Risk Factors

of Atherosclerosis

Jiang Xie, Haitao Wang, Jiyuan Zhang, Chao

Meng, Yanyan Kong, Shanping Mao, Lingyu

Xu, and Wu Zhang

Using Machine Learning to Predict Obesity in High School Students Zeyu Zheng and Karen Ruggiero

Preliminary Exploratory Data Analysis of National Clinical Data

Research Network to Induce Data Driven Phenotypes for Future Use

in Annotation of a Rare Tumor Biobanking Initiative

Alex Felmeister, Angela Waanders, Sarah

Leary, Jeffrey Stevens, Jennifer Mason, Rachel

Teneralli, Xiaohua Hu, and Charles Bailey

Low Computational Complexity Classifier Based on the Maximum

Relative Global Peak for the Classification of EOG Signals Akram Marseet, Shitij Kumar,, and Ferat Sahin

Optimizing Genetic Algorithm for Protein Crystallization Screening

using an Exploratory Fitness Function

Bidhan Bhattarai, Midusha Shrestha, Marc

Pusey, and Ramazan Aygun

Object Detection Technique for Malaria Parasite in Thin Blood Smear

Images

Priyadarshini Adyasha Pattanaik, Tripti

Swarnkar, and Debdoot Sheet



Workshop on Data Analytics in Metagenomics

Session Chair: Dr. Haiying Wang


2:10-2:40 Invited talk: Would phylogeny-aware classification achieve a better performance?

Prof. Huiru(Jane) Zheng

2:40-3:40 Session II (approximately 20 mins for each talk)

Machine Learning Approaches for Cyanobacteria Bloom Prediction

using metagenomic sequence data, a case study

JianDong Huang, Huiru (Jane) Zheng, Haiying

Wang, and Xingpeng Jiang

32

A Systems Biology Approach for Modeling Microbiomes Using Split

Graphs

Suyeon Kim, Ishwor Thapa, Guoqing Lu,

Lifeng Zhu, and Hesham Ali

Evaluation of the Oral Microbiome as a Biomarker for Early

Detection of Human Oral Carcinomas Julia Sommer and Hesham Ali

3:40 – 4:00 Coffee break

4:00– 4:20 The Modularity of Microbial Interaction Network in Healthy Human

Saliva: Stability and Specificity

Xiaohua Hu, Tingting He, Haiying Wang, Dan

Liu, Xingpeng Jiang, Huiru (Jane) Zheng, and

Bo Xie

4:20– 4:40 A Metagenomics Analysis of Rumen Microbiome

Paul Walsh, Cintia Palu, Brian Kelly, Brendan

Lawor, Jyotsna Wassan, Huiru (Jane) Zheng,

and Haiying Wang

4:40– 4:45 Closing Remarks

Workshop on Semantic Data Analytics and Machine learning in Bioinformatics and Medical

Informatics Session Chair: Dr. Haiying Wang



9:05 – 9:40 Invited talk: Biological Network Comparison

Prof. Pietro Hiram Guzzi

9:40 – 10:00 The Ontology Reference Model for Visual Selectivity Analysis in Drug-

target Interactions

Qiong Cheng, Felix Lopez, Celia Duran,

Christopher Camarillo, Tudor Oprea, and

Stephan Schurer


10:20-12:20 Session I (approximately 20 mins for each talk)

A Novel Hybrid Subset-Learning Method for Predicting Risk Factors of

Atherosclerosis

Jiang Xie, Haitao Wang, Jiyuan Zhang, Chao

Meng, Yanyan Kong, Shanping Mao, Lingyu

Xu, and Wu Zhang

Using Machine Learning to Predict Obesity in High School Students Zeyu Zheng and Karen Ruggiero

Preliminary Exploratory Data Analysis of National Clinical Data

Research Network to Induce Data Driven Phenotypes for Future Use in

Annotation of a Rare Tumor Biobanking Initiative

Alex Felmeister, Angela Waanders, Sarah Leary,

Jeffrey Stevens, Jennifer Mason, Rachel

Teneralli, Xiaohua Hu, and Charles Bailey

Low Computational Complexity Classifier Based on the Maximum

Relative Global Peak for the Classification of EOG Signals Akram Marseet, Shitij Kumar,, and Ferat Sahin

Optimizing Genetic Algorithm for Protein Crystallization Screening

using an Exploratory Fitness Function

Bidhan Bhattarai, Midusha Shrestha, Marc

Pusey, and Ramazan Aygun

Object Detection Technique for Malaria Parasite in Thin Blood Smear

Images

Priyadarshini Adyasha Pattanaik, Tripti

Swarnkar, and Debdoot Sheet


33


Workshop on Data Analytics in Metagenomics

Session Chair: Dr. Haiying Wang


2:10-2:40 Invited talk: Would phylogeny-aware classification achieve a better performance?

Prof. Huiru(Jane) Zheng

2:40-3:40 Session II (approximately 20 mins for each talk)

Machine Learning Approaches for Cyanobacteria Bloom Prediction

using metagenomic sequence data, a case study

JianDong Huang, Huiru (Jane) Zheng, Haiying

Wang, and Xingpeng Jiang

A Systems Biology Approach for Modeling Microbiomes Using Split

Graphs

Suyeon Kim, Ishwor Thapa, Guoqing Lu, Lifeng

Zhu, and Hesham Ali

Evaluation of the Oral Microbiome as a Biomarker for Early Detection

of Human Oral Carcinomas Julia Sommer and Hesham Ali

3:40 –4:00 Coffee break

4:00 – 4:20 The Modularity of Microbial Interaction Network in Healthy Human

Saliva: Stability and Specificity

Xiaohua Hu, Tingting He, Haiying Wang, Dan

Liu, Xingpeng Jiang, Huiru (Jane) Zheng, and

Bo Xie

4:20 – 4:40 A Metagenomics Analysis of Rumen Microbiome

Paul Walsh, Cintia Palu, Brian Kelly, Brendan

Lawor, Jyotsna Wassan, Huiru (Jane) Zheng,

and Haiying Wang

4: 40 – 4:45 Closing Remarks

The 8th Workshop on Integrative Data Analysis in Systems Biology (IDASB 2017)

Date: November 13, 2017; Location: Room 4; Each talk: 20 min including Q/A

Workshop Chairs: Zhongming Zhao, Rui Jiang, Huiru Jane Zheng


8:50-9:00 Opening Remarks Zhongming Zhao

Session I: Networks and Pathways (Chair: Zhongming Zhao)

9:00-9:20 A Graph-based Algorithm for Prioritizing Cancer

Susceptibility Genes from Gene Fusion Data

Xuanping Zhang, Mingzhe Xu, Yixuan Wang, Aiqing Gao,

Zhongmeng Zhao, Yi Huang, Xiao Xiao, and Jiayin Wang

9:20-9:40 A network-based approach to mine temporal genes exhibiting

significant expression variation in Caenorhabditis elegans

(S24201)

Kathryn Cooper, Wail Hassan, and Hesham Ali

9:40-10:00 Predicting Disease-causing Genes by using Domain

Interaction Network

Xianjun Shen, Xue Gong, Yang Yi, Xingpeng Jiang,

Tingting He, and Xiaohua Hu


Session II Feature Selection, Modeling, and Clustering (Chair: Rui Jiang)

34

10:20-10:40 A Convex Multi-view Low-Rank Sparse Regression for

Feature Selection and Clustering

Yao Lu, Jin-Xing Liu, Xiang-Zhen Kong, and Jun-Liang

Shang,

10:40-11:00 LJELSR: A Strengthened Version of JELSR for Feature

Selection and Clustering

Sha-Sha Wu, Mi-Xiao Hou, Chun-Mei Feng, and Jin-Xing

Liu

11:00-11:20 Pysubsim-tree: a package for simulating tumor genomes

according to tumor evolution history

Chu Yanshuo, Wang Ling, Wang Rongjie, Teng

Mingxiang, and Yadong Wang

11:20-11:40 Differential alternative splicing patterns with differential

expression to computationally extract plant molecular

pathways

Gaurav Kandoi and Julie Dickerson

11:40-12:00 TrapRM: Transcriptomic and Proteomic Rule Mining Using

Weighted Shortest Distance Based Multiple Minimum

Supports for Multi-Omics Dataset

Saurav Mallik and Zhongming Zhao

12:00-1:40 Lunch

Session III Systems Medicine in Disease Studies (Chair: Yunyun Zhou)

1:40-2:00 Pattern analysis of the interaction of regional amyloid load,

cortical thickness and APOE genotype in the progression of

Alzheimer’s disease

Chunfei Li, Chen Fang, Mercedes Cabrerizo, Armando

Barreto, Jean Andrian, David Loewenstein, Ranjan Duara,

and Malek Adjouadi

2:00-2:20 VariFunNet, an integrated multiscale modeling framework to

study the effects of rare non-coding variants in Genome-Wide

Association Studies: applied to Alzheimer’s Disease

Qiao Liu, Chen Chen, Annie Gao, Hang Hang Tong, and

Lei Xie

2:20-240 Identification of Novel Therapeutic Targets in

Myelodysplastic Syndrome Using Gene Expression Datasets

and Protein-Protein Interaction Approach

ARIF ALI, Muhammad Junaid, Abbas Khan, Abdul

Wadood, and Dongqing Wei

2:40-3:00 Digestive Functions Regulated by 6-shogaol Towards Stomach

and Small Intestine

Guang Zheng

3:00-3:20 Novel gene selection method for breast cancer intrinsic

subtypes from two large cohort study

Silu Zhang, Yin-yuan Mo, Torumoy Ghoshal, Dawn

Wilkins, Yixin Chen, and Yunyun Zhou

3:20-3:40 scDNA: a fast and comprehensive tool for single cell-based

differential network analysis

Yu-Chiao Chiu, Yidong Chen, Li-Ju Wang, and Tzu-Hung

Hsiao


Session IV Algorithms and Computational Tools (Chair: Huiru Jane Zheng)

4:00-4:20 Cavatica: a pipeline for identifying author adoption trends

among software or methods

Jennifer Chang and Hui-Hsien Chou

4:20-4:40 AProvBio: An Architecture for Data Provenance in

Bioinformatics Workflows using Graph Database

Rodrigo Almeida, Maristela Holanda, Aleteia Araujo,

Klayton Castro, Maria Emília Walter, Waldeyr Silva, and

Sergio Lifschitz

4:40-5:00 NanoStringBioNet: Integrated R Framework for Bioscience

Knowledge Discovery from NanoString nCounter Data

Mariah Hoffman, Carrie Minette, Shanta Messerli, Ratan

Bhardwaj, and Etienne Gnimpieba

5:00-5:10 Closing Remarks Huiru Jane Zheng

35

Conference Paper Presentations

Session 1 Genomics

Regular

B324 "Multiplex Confounding Factor Correction for Genomic Association Mapping with Squared

Sparse Linear Mixed Model"

Haohan Wang, Xiang Liu, Yunpeng Xiao, Ming Xu, and Eric Xing

Regular B508 "A New Statistical Model for Genome-Scale MicroRNA Target Prediction"

Zeynep Hakguder, Chunxiao Liao, Jiang Shu, and Quan Cui

Regular B506 "Unraveling Complex Local Genomic Rearrangements From Long-Read Data"

Zachary Stephens, Ravishankar Iyer, Chen Wang, and Jean-Pierre Kocher

Short B529 "DiCE: Discovery of Conserved Noncoding Sequences Efficiently"

Sairam Behera, Jitender S. Deogun, Xianjun Lai, and James C Schnable

Short B570 "HiCComp: Multiple-level Comparative Analysis of Hi-C Data by Triplet Network"

Yan Zhang, Bo Zhang, W. Jim Zheng, Jijun Tang, and Feng Yue

Session 2 Biological Networks

Regular

B312 "Integrating embeddings of multiple gene networks to prioritize complex disease-associated

genes"

Mengmeng Wu, Wanwen Zeng, Wenqiang Liu, Yijia Zhang, Ting Chen, and Rui Jiang

Regular B362 "Microbial Co-presence and Mutual-exclusion Networks in the Bovine Rumen Microbiome"

Haiying Wang, Huiru (Jane) Zheng, Richard J. Dewhurst, and Rainer Roehe

Regular B416 "GMAlign: a new network aligner for revealing large conserved functional components"

Yuanyuan Zhu, Yuezhi Li, Juan Liu, Lu Qin, and Jeffrey Xu Yu

Short B300 "Using Multi-level Petri Nets Models to Simulate Microbiota Resistance to Antibiotics"

Roberta Bardini, Gianfranco Politano, Alfredo Benso, and Stefano Di Carlo

Short B342 "Mathematical model for pancreatic cancer progression using non-constant gene mutation rate"

Shuhao Sun, Fima Klebaner, and Tianhai Tian

Short

B562 "Sleep/wake state prediction and sleep parameter estimation using unsupervised classification

via clustering"

Yasser El-Manzalawy, Orfeu Buxton, and Vasant Honavar

Short

B591 "MicroRNA Dysregulational Synergistic Network: Learning Context-Specific miRNA

Dysregulations in Lung Cancer Subtypes"

Nhat Tran, Vinay Abhyankar, Kytai Nguyen, Ishfaq Ahmad, Jon Weidanz, and Jean Gao

36

Session 3 Medical Informatics I

Regular B427 "Topic Medical Concept Embedding: Multi-Sense Representation Learning for Medical Concept"

Feng Qian, Chengyue Gong, Luchen Liu, Lei Sha, and Ming Zhang

Regular B273 "Modeling Heart Procedures from EHRs: An Application of Exponential Families"

Shuo Yang, Fabian Hadiji, Kristian Kersting, Shaun Grannis, and Sriraam Natarajan

Regular B402 "Improving Palliative Care with Deep Learning"

Anand Avati, Kenneth Jung, Stephanie Harman, Lance Downing, Andrew Ng, and Nigam Shah

Short

B620 "Computerized Neuropsychological Assessment in Mild Cognitive Impairment Based on Natural

Language Processing-oriented Feature Extraction"

Chen Fang, Panuwat Janwattanapong, Harold Martin, Mercedes Cabrerizo, Armando Barreto, David

Loewenstein, Ranjan Duara, and Malek Adjouadi

Short

B272 "A Gaussian Discriminant Analysis-based Generative Learning Algorithm for the Early Diagnosis

of Mild Cognitive Impairment in Alzheimer’s Disease"

Chen Fang, Chunfei Li, Mercedes Cabrerizo, Armando Barreto, Jean Andrian, David Loewenstein,

Ranjan Duara, and Malek Adjouadi

Session 4 Biomedical Text Mining I

Regular

B223 "Combine biological experiments, statistical analysis, and semantic search to discover association

among high-sensitive C-reactive protein, body fat mass distribution, and other cardiometabolic risk

factors in young healthy women"

Bin Wu, Jingshan Huang, Mohan Kasukurthi, Fangwan Huang, Jiang Bian, Keisuke Fukuo, Kazuhisa

Suzuki, Gen Yoshino, and Tsutomu Kazumi

Regular

B226 "Biomedical Named Entity Recognition Based on the Two Channels and Sentence-level Reading

Control Conditioned LSTM-CRF"

Lishuang Li and Yuxin Jiang

Regular B239 "The application of machine learning to evaluate the adequacy of information in radiology orders"

Wasim Al Assad, Max Topaz, John Tu, and Li Zhou

Short B214 "Discovering Additional Complex NCIt Gene Concepts with High Error Rate"

Ling Zheng, Hua Min, Yehoshua Perl, and James Geller

Short B252 "A deep network based integrated model for disease named entity recognition"

Fan Tong, Zheheng Luo, and Dongsheng Zhao

Short

B383 "Drug Drug Interaction Extraction from Literature Using a Skeleton Long Short Term Memory

Neural Network"

Zhenchao Jiang, Liang Gu, and Qingshan Jiang

Short B502 "Novel Algorithms for Finding the Closest l-mers in Biological Data"

Xingyu Cai, Abdullah-Al Mamun, and Sanguthevar Rajasekaran

37

Session 5 Translational Bioinformatics, Cheminformatics and pharmacogenomics

Regular B469 "A Multimodal Deep Architecture for Large Scale Protein Ubiquitylation Site Prediction"

Fei He, Lingling Bao, Rui Wang, Jiagen Li, Dong Xu, and Xiaowei Zhao

Regular

B531 "Feature weighting for antimicrobial peptides classification: a multi-objective evolutionary

approach"

Jesus Beltran, Longendri Aguilera-Mendoza, and Carlos Brizuela

Regular

B326 "THCluster:Herb Supplements Categorization for Precision Traditional Chinese Medicine"

Chunyang Ruan, Ye Wang, Yanchun Zhang, Jiangang Ma, Huijuan Chen, Uwe Aickelin, Shanfeng Zhu,

and Ting Zhang

Short B446 "A Molecular Docking Platform Based on Hadoop"

Yueli Dong

Short

B321 "Retrieval of Promiscuous Natural Compounds using Multiple Targets Docking Strategy: A Case

Study on Kinase Polypharmacology"

Chirag Patel, Siva Kumar Prasanth Kumar, Krunal Modi, Daxesh Patel, Frank Gonzalez, and

Himanshu Pandya

Session 6 Structure, Function and Evolution I

Regular B207 "Reconstructing and Mining Protein Energy Landscapes to Understand Disease"

Wanli Qiao, Tatiana Maximova, Xiaowen Fang, Erion Plaku, and Amarda Shehu

Regular B296 "Confidence assessment of protein-DNA complex models"

Rosario Corona, Sanjana Sudarshan, Srinivas Aluru, and Jun-tao Guo

Regular

B318 "BiRWLGO: A global network-based strategy for lncRNA function annotation using bi-random

walk"

Jingpu Zhang, Shuai Zou, and Lei Deng

Short B240 "RUPEE: Scalable Protein Structure Search using Run Position Encoded Residue Descriptors"

Ron Ayoub and Yugyung Lee

Short B242 "Analyzing T Cell Receptor Alpha/Beta Usage in Binding to the pMHC"

Ryan Ehrlich and Dario Ghersi

Session 7 Semantics and Ontology

Regular

B471 "DeepText2Go: Improving Large-scale Protein Function Prediction with Deep Semantic Text

Representation"

Ronghui You and Shanfeng Zhu

Regular B548 "DIR - A Semantic Information Resource for Healthcare Datasets"

Jingyi Shi, Mingna Zheng, Lixia Yao, and Yaorong Ge

Short B571 "Generating Abstraction Networks using Semantic Similarity Measure of Ontology Concepts"

David Cirella and Huanying Gu

Short B587 "Constructing Dynamic Ontologies from Biomedical Publications"

Megha Nagabhushan, Rohithkumar Nagulapati, Mayanka Chandrashekar, and Yugyung Lee

38

Short

B495 "Discover the Semantic Structure of Human Reference Epigenome by Differential Latent Dirichlet

Allocation"

Yiyu Zheng, Xiaoman Li, and Haiyan Hu

Session 8 Medical Informatics II

Regular B330 "Distributed Gene Clinical Decision Support System Based on Cloud Computing"

Bo Xu, Changlong Li, Hang Zhuang, Jiali Wang, Qingfeng Wang, Chao Wang, and Xuehai Zhou

Regular B535 "Signature-Based Clustering for Analysis of the Wound Microbiome"

Timothy Chappell, Shlomo Geva, James Hogan, Flavia Huygens, Wayne Kelly, and Dimitri Perrin

Short

B336 "Normalized Mutual Information Feature Selection for Electroencephalogram Data based on

Grassberger Entropy Estimator"

Xiaowei Zhang, Yuan Yao, Manman Wang, Jian Shen, Lei Feng, and Bin Hu

Short

B558 "QA Diagnostics with Visual Recognition Tracking for Accurate Trending of Alzheimer’s

Disease"

Matthew Velazquez and Yugyung Lee

Short B477 "Optimizing Inpatient Bed Capacity to Improve Care Delivery"

Eva Lee and Andriy Shapoval

Short

B560 "Telerehabilitation System to Support Multipronged Exercise in Patients with Multiple

Sclerosis"

Jeffrey Wood and Joseph Finkelstein

Session 9 Structure, Function and Evolution II

Regular

B403 "Discovery and Disentanglement of Protein Aligned Pattern Clusters to Reveal Subtle Functional

Subgroups"

Pei-Yuan Zhou, Antonio Sze-Tzo, and Andrew K.C. Wong

Regular B475 "Effective Small Interfering RNA Design based on Convolutional Neural Network"

Ye Han, Fei He, Xian Tan, and Helong Yu

Regular B546 "Pattern-Directed Aligned Pattern Clustering"

Antonio Sze-To and Andrew K.C. Wong

Regular B595 "Structure-Based Protein Family Signature: Efficient Comparison of Multidomain Proteins"

Jun Tan and Donald Adjeroh

Regular B519 "Differential gene expression analysis in single-cell RNA sequencing data"

Tianyu Wang and Sheida Nabavi

Short

B279 "HIV1 - Human Protein-protein Interaction Prediction Based on Interface Architecture

Similarity"

Chunyu Zhao, Yizhou Zang, Wei Quan, Xiaohua Hu, and Ahmet Sacan

Short

B439 "Combining diffusion and HeteSim features for accurate prediction of protein-lncRNA

interactions"

Junqiang Wang, Yun Xiao, Zixiang Wang, Weihua Zhan, and Lei Deng

Short

B478 "Co-expression networks between protein encoding mitochondrial genes and all the remaining

genes in human tissues"

João Almeida, Joana Ferreira, Rui Camacho, and Luísa Pereira

39

Session 10 Next-Gen Sequencing

Regular

B364 "MEC: Misassembly Error Correction in contigs using a combination of paired-end reads and

GC-contents"

Binbin Wu, Jianxin Wang, Junwei Luo, Min Li, Fang-Xiang Wu, and Yi Pan

Regular

B492 "Noise Cancellation for Robust Copy Number Variation Detection Using Next Generation

Sequencing Data"

Fatima Zare, Sardar Ansari, Kayvan Najarian, and Sheida Nabavi

Regular B611 "Comparative Analysis of Alignment Tools for Nanopore Reads"

Natasha Pavlovikj, Etsuko Moriyama, and Jitender Deogun

Regular B609 "LiDiAimc: LincRNA-Disease Associations through Inductive Matrix Completion"

Ashis Biswas and Jean Gao

Short

B334 "Pre-SCNAClonal: efficient GC bias correction for SCNA based tumor subclonal populations

inferring"

Chu Yanshuo, Teng Mingxiang, Wang Zhenxing, Wang Yongtian, and Yadong Wang

Short B425 "A copy-number variation detection pipeline for single cell sequencing data on BGI Online"

Jingying Huang, Yuwen Zhou, Aodan Xu, Enhong Zhuo, Xin Jin, and Hongmin Cai

Short B501 "Probabilistic Estimation of Overlap Graphs for Large Sequence Datasets"

Rahul Nihalani, Sriram Chockalingam, Shaowei Zhu, Vijay Vazirani, and Srinivas Aluru

Session 11 Biomedical Text Mining II

Regular

B309 "Analysis of the Consistency in the Structural Modeling of SNOMED CT and CORE Problem

List Concepts"

Ankur Agrawal and Paul Revelo

Regular

B327 "Cascade Word Embedding to Sentence Embedding: A Class Label Enhanced Approach to

Phenotype Extraction"

Wenhui Xing, Xiaohui Yuan, Lin Li, and Jing Peng

Regular B557 "Bacteria Named Entity Recognition based on Dictionary and Conditional Random Field"

Xiaoyan Wang, Xingpeng Jiang, Mengwen Liu, Tingting He, and Xiaohua Hu

Regular B613 "CDRnN: a high performance Chemical-Disease Recognizer in biomedical literature"

Hsin-Chun Lee and Hung-Yu Kao

Short

B289 "Exploiting Argument Information to Improve Biomedical Event Trigger Identification via

Recurrent Neural Networks and Supervised Attention Mechanisms"

Lishuang Li and Yang Liu

Short B305 "FNSemSim: an improved disease similarity method based on network fusion"

Yongtian Wang, Liran Juan, Yanshuo Chu, Rongjie Wang, Tianyi Zang, and Yadong Wang

40

Session 12 Microarray, SNPs and Haplotype Analysis, GWAS, Personalized Genomics

Regular B447 "Statistical Selection of Biological Models for Genome-Wide Association Analyses"

Wenjian Bi, Guolian Kang, and Stanley Pounds

Regular

B476 "MiteFinder: A fast approach to identify miniature inverted-repeat transposable elements on a

genome-wide scale"

Jialu Hu, Yan Zheng, and Xuequn Shang

Regular B559 "Inversion Detection Using PacBio Long Reads"

Shenglong Zhu, Scott Emrich, and Danny Chen

Regular B603 "What Can One Chromosome Tell us About Human Biogeographical Ancestry?"

Tanjin Taher Toma, Zachary Williams, Donald Adjeroh, and Jeremy Dawson

Regular B504 "Choosing optimal controls for genotyping arrays"

John Sigmon and Leonard McMillan

Short

B481 "Genetic Variant Analysis of Boys with Autism: a Pilot Study on Linking Facial Phenotype to

Genotype"

Tayo Obafemi-Ajayi, Luke Settles, Yuqing Su, Gayla Olbricht, Cynthia Germeroth, T. Nicole

Takahashi, Judith Miles, and Donald Wunsch

Short

B521 "Modeling SNP and Quantitative Trait Association from GWAS Catalog Using CLG Bayesian

Network"

Lu Zhang, Qiuping Pan, and Xintao Wu

Session 13 Computational Modeling and Data Integration I

Regular B260 "The relative importance of data points in systems biology and parameter estimation"

Jenny Jeong and Peng Qiu

Regular

B453 "POST: a framework for set-based association analysis in high-dimensional data"

Xueyuan Cao, E. Olusegun George, Mingjuan Wang, Dale Armstrong, Cheng Cheng, Susana

Raimondi, Jeffrey Rubnitz, James Downing, Mondira Kundu, and Stanley Pounds

Regular

B313 "A Spectrum Graph-Based Filtering Algorithm for Proteoform Identification by Top-Down

Mass Spectrometry"

Runmin Yang, Daming Zhu, Qiang Kou, Poornima Bhat-Nakshatri, Harikrishna Nakshatri, Si Wu, and

Xiaowen Liu

Short B315 "Predicting small RNAs in bacteria via sequence learning ensemble method"

Wen Zhang, Jingwen Shi, Guifeng Tang, Wenjian Wu, Xiang Yue, and Dingfang Li

Short B488 "Granularity-Aware Fusion of Biological Networks for Information Extraction"

Sean West and Hesham Ali

41

Short

B520 "Deterministic Convection-Diffusion Approach for Modeling Cell Motion and Spatial

Organization: experimentation on avascular tumor growth"

Cheikhou Oumar KA, Jean-Marie Dembélé, Christophe Cambier, Serge Stinckwich, Moussa Lo, and

Jean-Daniel Zucker

Short B483 "Modeling metabolic rewiring during melanoma progression using Flux Balance Analysis"

Rahul Metri, Shikhar Saxena, Madhulika Mishra, and Nagasuma Chandra

Short B244 "Improved Classification Model for Peptide Identification Based on Self-paced Learning"

Yongxiang Wang, Xijun Liang, Zhonghang Xia, Xinnan Niu, Andrew J. Link, and Haiqing Yin

Session 14 AI and Machine Learning Methods in Biomedical Informatics I

Regular

B251 "BpMC: A Novel Algorithm Retrieving Multilayered Tissue Bio-optical Properties for Non-

invasive Blood Glucose Measurement"

Weijie Liu, Anpeng Huang, and Ping Wang

Regular

B284 "Mapping Client Messages to a Unified Data Model with Mixture Feature Embedding

Convolutional Neural Network"

Dingcheng Li, Peini Liu, Ming Huang, Yu Gu, Yue Zhang, Xiaodi Li, Daniel Dean, Xiaoxi Liu, Jingmin

Xu, Hui Lei, and Yaoping Ruan

Regular B293 "Predicting drug-disease associations based on the known association bipartite network"

Wen Zhang, Xiang Yue, Yanlin Chen, Weiran Lin, Bolin Li, Feng Liu, and Xiaohong Li

Regular B322 "IMAP: An Iterative Method for Aligning Protein-Protein Interaction Networks"

Xuezhi Cao, Zhiyu Chen, Xinyi Zhang, and Yong Yu

Regular

B325 "Variable Selection in Heterogeneous Datasets: A Truncated-rank Sparse Linear Mixed Model

with Applications to Genome-wide Association Studies"

Haohan Wang, Bryon Aragam, and Eric Xing

Short B355 "Stable Feature Ranking with Logistic Regression Ensembles"

Ronald Nowling and Scott Emrich

Session 15 Biomedical Intelligence, Clinical Data Analysis

Regular

B217 "A Bag-of-Words Approach for Assessing Activities of Daily Living using Wrist Accelerometer

Data"

Matin Kheirkhahan, Shikha Mehta, Madhurima Nath, Amal Wanigatunga, Duane Corbett, Todd

Manini, and Sanjay Ranka

Regular

B368 "Assessing Chronic Kidney Disease from Office Visit Records Using Hierarchical Meta-

Classification of an Imbalanced Dataset"

Moumita Bhattacharya, Claudine Jurkovitz, and Hagit Shatkay

Regular

B588 "Collaborations across disciplines: MU Thyroid Nodule Electronic Database (MU-TNED), a

multidisciplinary informatics approach"

Terri Benskin, Iris Zachary, Magda Esebua, and Uzma Khan

Short B219 "Causal Effect Study of High Cholesterol on Myopia"

Diyue Bu and Xuefu Wang

42

Short B281 "Using Mutual Information Clustering to Discover Food Allergen Cross-Reactivity"

Kenneth Lai, Suzanne Blackley, and Li Zhou

Short B392 "Context Preserving Representation of Daily Activities in Elder Care"

Omar Ibrahim, James Keller, and Mihail Popescu

Session 16 Biomedical Signal/Image Analysis I

Regular

B243 "Superresolution and EM based ML Kalman Estimation of the Stochastic Microtubule Signal

Modeled as Three States Random Evolution"

Vineetha Menon, Shantia Yarahmadian, and Vahid Rezania

Regular

B271 "A Novel Wavelet-based Model for EEG Epileptic Seizure Detection using Multi-context

Learning"

Ye Yuan, Guangxu Xun, Kebin Jia, and Aidong Zhang

Short B216 "Diagnosis of Cirrhosis Stage via Deep Neural Network"

Zhiping Xu, Xiang Liu, Xi En Cheng, Jia Lin Song, and Jian Quan Zhang

Short

B245 "3D intracranial artery segmentation using a convolutional autoencoder"

Li Chen, Yanjun Xie, Jie Sun, Niranjan Balu, Mahmud Mossa-basha, Kristi Pimentel, Thomas

Hatsukami, Jenq-neng Hwang, and Chun Yuan

Short

B261 "A Stochastic Iterative Evolution CT Reconstruction Algorithm for Limited-Angle Sparse

Projection Data"

Lan Luo, Hongxia Gao, Yinghao Luo, and Yongfei Chen

Short B299 "Left Ventricle Motion Estimation for Cardiac Cine MRI Using Graph Matching"

Wei Guo, Xuan Yang, Junhao Wu, and Adan Lin

Short

B283 "Classifying Continuous Hand Grips and Movements Using Myoelectric and Accelerometer

Signals"

Gene Shuman, Zoran Duric, and Lynn H. Gerber

Session 17 AI and Machine Learning Methods in Biomedical Informatics II

Regular B328 "Biomedical Event Trigger Detection Based on Bidirectional LSTM and CRF"

Yan Wang, Jian Wang, Hongfei Lin, Shaowu Zhang, and Lishuang Li

Regular

B389 "Down Syndrome Prediction/Screening Model Based on Deep Learning and Illumina

Genotyping Array"

Bing Feng, William Hoskins, Yan Zhang, Zibo Meng, David Samuels, Yan Guo, and Jijun Tang

Regular

B419 "Single-trial classification of fNIRS signal measured from prefrontal cortex during four

directions motor imagery task"

Bin Hu, Hong Peng, Jinlong Chao, Yongzong Wang, and Majoe Dennis

43

Regular

B451 "Microaneurysm Detection in Fundus Images by Small Image Patches and Machine Learning

Methods"

Wen Cao, Nicholas Czarnek, Juan Shan, and Lin Li

Regular B236 "Ensemble Graphs to Reveal Post-Transcriptional Regulatory Networks in Alzheimer's Disease"

Ruben Armananzas

Short B417 "Multi-Label learning by exploiting label correlations for TCM Diagnosing Parkinson’s Disease"

Yue Peng, Chi Tang, Gang Chen, Junyuan Xie, and Chongjun Wang

Session 18 Biomedical Signal/Image Analysis II

Regular

B567 "Knee Osteoarthritis Prediction on MR Images Using Cartilage Damage Index and Machine

Learning Methods"

Yaodong Du, Juan Shan, and Ming Zhang

Regular B579 "Whole Mammogram Image Classification With Convolutional Neural Networks"

Xiaofei Zhang, Yi Zhang, Erik Han, Nathan Jacobs, Qiong Han, Xiaoqin Wang, and Jinze Liu

Short

B357 "Left Ventricle Segmentation by Combining Convolution Neural Network with Active Contour

Model and Tensor Voting in Short-axis MRI"

Zewen Li, Adan Lin, Xuan Yang, and Junhao Wu

Short B378 "Deep Learning Assessment of Tumor Proliferation in Breast Cancer Histological Images"

Manan Shah, Dayong Wang, Christopher Rubadue, David Suster, and Andrew Beck

Short

B408 "APOE4 Modulates the Activities Within Defalut Mode Network and Interactions of Resting

Intrinsic Networks"

Zhijun Yao, Bin Hu, Tao Hu, Jianping An, Dawei Song, and Ning Zhong

Short

B547 "Cytological Malignancy Grading Systems for Fine Needle Aspiration Biopsies of Breast

Cancer"

Muneera Alsaedi, Thomas Fevens, Adam Krzyzak, and Lukasz Jelen

Short

B562 "Sleep/wake state prediction and sleep parameter estimation using unsupervised classification

via clustering"

Yasser El-manzalawy, Orfeu Buxton, and Vasant Honavar

Session 19 Clinical Decision Support and Informatics

Regular

B612 "Comprehensive Analysis of Pulmonary Adenocarcinoma in Situ (AIS) Revealed New Insights

into Lung Cancer Progression"

Dan Li, William Yang, Yifan Zhang, Jack Y. Yang, Weida Tong, Renchu Guan, and Mary Qu Yang

Short B316 "An Interpretable Model for Predicting Side Effects of Analgesics for Osteoarthritis"

Liangliang Liu, Jianxin Wang, Min Li, Fang-Xiang Wu, HongDong Li, Ying Yu, and Zhihui Fei

Short

B363 "Change-Point Detection for Monitoring Clinical Decision Support Systems with a Multi-

Process Dynamic Linear Model"

Siqi Liu, Adam Wright, Dean Sittig, and Milos Hauskrecht

44

Short B459 "Discriminative Boosted Bayes Networks for Learning Multiple Cardiovascular Procedures"

Nandini Ramanan, Shuo Yang, Shaun Grannis, and Sriraam Natarajan

Short B400 "Stroke Patient Daily Activity Observation System"

Jaired Collins, Joseph Warren, Mengxuan Ma, Rachel Proffitt, and Marjorie Skubic

Short B617 "A Novel Resource Management Approach for Paramedic Triage Systems"

Subrata Acharya and Omotayo Imani

Session 20 Healthcare Informatics I

Regular B266 "Joint Learning of Representations of Medical Concepts and Words from EHR Data"

Tian Bai, Ashis Chanda, Brian Egleston, and Slobodan Vucetic

Regular

B467 "Patient Outcome Prediction via Convolutional Neural Networks based on Multi-Granularity

Medical Concept Embedding"

Yujuan Feng, Xu Min, Ning Chen, Hu Chen, Xiaolei Xie, Haibo Wang, and Ting Chen

Regular

B527 "Learning Rich Geographical Representations: Predicting Colorectal Cancer Survival in the State

of Iowa"

Michael Lash, Yuqi Sun, Xun Zhou, Charles Lynch, and Nick Street

Regular B365 "ImageSfERe: Image Sharing for Epilepsy Research"

Xi Wu, Steve Roggenkamp, Shiqiang Tao, and Guo-qiang Zhang

Short

B208 "A Self-adaptive 30-day Diabetic Readmission Prediction Model based on Incremental

Learning"

Peng Zhao and Illhoi Yoo

Short

B308 "Developing a Regional Classifier to Track Patient Needs in Medical Literature Using Spiral

Timelines on a Geographical Map"

Chunlei Tang, Haohan Zhang, Kenneth Lai, Yuxuan She, Yun Xiong, and Li Zhou

Short B374 "A New Dataset for Evaluating Pedometer Performance"

Ryan Mattfeld, Elliot Jesch, and Adam Hoover

Session 21 Computational Modeling and Data Integration II

Regular B566 "UPS: A New Approach for Multiple Sequence Alignment Using Morphing Techniques"

Quoc-Nam Tran and Mike Wallinga

Regular B580 "Integrate Multi-omic Data Using Affinity Network Fusion (ANF) for Cancer Patient Clustering"

Tianle Ma and Aidong Zhang

Regular B606 "ALL-CQS: Adaptive Locality-based Lossy Compression of Quality Scores"

Jiabing Fu and Shoubin Dong

Short B545 "Translating Literature into Causal Graphs: Toward Automated Experiment Selection"

Nicholas Matiasz, Justin Wood, Wei Wang, Alcino Silva, and William Hsu

45

Short B551 "Repairing gaps in Kinari-2 for large scale protein and flexibility analysis applications"

Magdalena Metlicka, Mojtaba Nouri Bygi, and Ileana Streinu

Session 22 AI and Machine Learning Methods in Biomedical Informatics III

Regular

B484 "Temporal Reflected Logistic Regression for Probabilistic Heart Failure Survival Score

Prediction"

Mingjie Qian, Jyotishman Pathak, Naveen L. Pereira, and Chengxiang Zhai

Regular B490 "Long Short-Term Memory Recurrent Neural Networks for Antibacterial Peptide Identification"

Michael Youmans, Christian Spainhour, and Peng Qiu

Regular B528 "Collaborative Phenotype Inference from Comorbid Substance Use Disorders and Genotypes"

Jin Lu, Jiangwen Sun, Xinyu Wang, Henry Kranzler, Joel Gelernter, and Jinbo Bi

Short

B530 "Prediction of Human QT Prolongation Liability Based on Pre-Clinical RNA Expression

Profiles"

Dennis Bergau, Cong Liu, and Hui Lu

Short

B538 "A Deep Learning Model for Predicting Tumor Suppressor Genes and Oncogenes from PDB

Structure"

Amirhossein Tavanaei, Nishanth Anandanadarajah, Anthony Maida, and Rasiah Loganantharaj

Short

B625 "Invited Talk: Developing Deep Multi-source Intelligent Learning that Facilitates the

Advancement of Single Cell Genomics Research"

William Yang, Sherman Weissman, Renchu Guan, Jialing Zhang, Allon Canaan, and Mary Qu Yang

Session 23 Healthcare Informatics II

Regular B385 "Predictive Deep Network with Leveraging Clinical Measure as Auxiliary Task"

Xiangrui Li, Dongxiao Zhu, and Phillip Levy

Regular B553 "Personalized Disease Prediction Using a CNN-Based Similarity Learning Method"

Qiuling Suo, Fenglong Ma, Ye Yuan, Mengdi Huai, Weida Zhong, Jing Gao, and Aidong Zhang

Regular

B614 "Toward the Precision Breast Cancer Survival Prediction Utilizing Combined Whole Genome-

wide Expression and Somatic Mutation Analysis"

Yifan Zhang, William Yang, Dan Li, Jack Y. Yang, Renchu Guan, Weida Tong, and Mary Qu Yang

Regular

B601 "Identifying Individuals Amenable to Drug Recovery Interventions through Computational

Analysis of Addiction Content in Social Media"

Ryan Eshleman, Deeptanshu Jha, and Rahul Singh

Short B583 "Spatio-Temporal Autoencoder for Feature Learning in Patient Data with Missing Observations"

Jia Yao, Chongyu Zhou, and Mehul Motani

46

Session 24 Biological Data Mining, Visualization, High Performance Computing

Regular

B458 "An Interactive Workflow Generator to Support Bioinformatics Analysis through GPU

Acceleration"

Anuradha Welivita, Indika Perera, and Dulani Meedeniya

Short

B401 "Visualization of Disease Relationships by Multiple Maps t-SNE Regularization Based on

Nesterov Accelerated Gradient"

Xianjun Shen, Xianchao Zhu, Xingpeng Jiang, Tingting He, and Xiaohua Hu

Short B232 "Optimal Codon Pair Bias Design"

Nolan Donoghue, Justin Gardin, Bruce Futcher, and Steven Skiena

Short B359 "A bucket index correction based method for compression of genomic sequencing data"

Rongjie Wang, Bai Yang, Qianlong Cheng, Tianyi Zang, and Yadong Wang

Short B610 "Efficient GPU-Accelerated Extraction of Imperfect Inverted Repeats from DNA Sequences"

William Baskett, Matt Spencer, and Chi-ren Shyu

Special Session on Medical Informatics and Engineering

SP01202 Zhenghao Guo, Hailiang Long, Hanshu Cai, Li Yao, and Xia Wu, Abnormal EEG-Based Functional

Connectivity under a Face-Word Stroop Task in Depression

SP01203 xun pu, Jinghang Chen, Chengyang Jing, Edwin Tawanda Mudzingwa, Yuan Xia, Yusheng Huan, Tingting Li,

Kun Lu, Ping Chen, and Le Zhang,Developing a localized web server for survival, generic and protein data

analysis with high performance computing technology

SP01204 Zirong Li and Lian Li, A novel method for lung masses detection and location based on deep learning

SP01205 Xingwang Liu, Mi Li, Shengfu Lu, Ming Zhang, Dachao Liu, Lei Feng, Bingbing Fu, Gang Wang, and Ning

Zhong, Eye Movement Pattern and Mental Retardation in Depression

SP01207 Junming Huang, Xiangmin Xu, and Tong Zhang, Emotion Classification Using Deep Neural Networks and

Emotional Patches

SP01208 Jingying Wang, Xiaoyun Sui, Jonathan Flint, and Tingshao Zhu, Identifying Comorbidities from Depressed

People via Voice Analysis

SP01210 Yiqiang Chen, Xiaodong Yang, Biao Chen, Chunyan Miao, and Hanchao Yu, PdAssist: Objective and

Quantified Symptom Assessment of Parkinson’s Disease via Smartphone

SP01211 Zhenyu Liu, Chongcong Li, Xiang Gao, Gang Wang, and Jing Yang, Ensemble-based Depression Detection in

Speech

SP01212 Guannan He, Yanchun Liang, Yan Chen, William Yang, Jun S. Liu, Mary Qu Yang, and Renchu Guan, Hot

Topics Discovery on Diabetes Mellitus and Obesity Using Representation Learning

47

Industry Session

N201 Tolgahan Cakaloglu, Medi-Deep: Deep Control in a Medication Usage

N202 Zhaohui Xu, Pooja Yadav, Zhizhou Zhang, Sankardas Roy, and Huimin Zhang, Quantification of Microbial Species in Solid State Fermentation Samples Using Signature Genomic Sequences

N203 Rengarajan Pelapur, V. B. Surya Prasath, Juan Moreno, and Michael Heck, 3D Workflow for Segmentation and Interactive Visualization in Brain MR images using Multiphase Active Contours

N204 Bingbing Liang, Wenyu Fan, Jing “Ginger” Han, Ning Chen, and Nan Zhao, An implementation of infants’ gut microbiome maturation analyses by 16s rRNA from stool samples in extraction solution of room temperature

N205 Chongsheng Zhang, Jingjun Bi, and Paolo Soda, Feature Selection and Resampling in Class Imbalance Learning: Which Comes First? An Empirical Study in the Biological Domain

N206 Qiuping Pan, Lu Zhang, and Xintao Wu, STIP: An SNP-Trait Inference Platform

N207 Shantanu Dev, Shinan Zhang, Joseph Voyles, and Anand Rao, Automated Classification of Adverse Events in Pharmacovigilance

Poster List

Poster

ID Poster Papers

P202 Ms Ijeoma Uzoma and Dr Emmanuel Nna, Detection of BCR-ABL1 gene in the saliva chronic myeloid leukaemic

patients

P204 Garry Wong, Novel Tumor Biomarker based on isomiR expression profiles

P205 Hongwei Ge, Liang Sun, Yao Yao, and Jinghong Yu, An automatic motif recognition algorithm in DNA sequences

based on particle swarm optimization and random projection

P206 Alisa Kazarina, Guntis Gerhards, Elina Petersone-Gordina, Ilva Pole, Viktorija Igumnova, Janis Kimsis, Valentina

Capligina, and Renate Ranka, Insights into archaeological human sample microbiome using 16S rRNA gene

sequencing

P208 Suraj Subedi, Marc Pusey, and Ramazan Aygun, Visual-X2: Scoring and Visualization Tool for Analysis of Protein

Crystallization Trial Images

P209 Rohan Koodli, On the Robustness of Mixture Model-based Unsupervised Learning in Single-Cell Analyses

P210 V. B. Surya Prasath and Hiroharu Kawanaka, Near-Light Perspective Shape from Shading for 3D Visualizations in

Endoscopy Systems

P212 Pasan Fernando, Laura Jackson, James Balhoff, Erliang Zeng, and Paula Mabee, A generic bioinformatics pipeline to

integrate large-scale trait data with large phylogenies

48

P213 Raghvendra Mall, Ehsan Ullah, Khalid Kunji, Michele Ceccarelli, and Halima Bensmail, An Adaptive Refinement for

Community Detection Methods for Unsupervised Disease Module Identification in Biological Networks using Novel Quality Metric based on Connectivity, Conductance and Modularity

P214 Ehsan Ullah, Saila Shama, Noora Al Muftah, Ian Thompson, Reda Rawi, Raghvendra Mall, and Halima

Bensmail, Identification of Cancer Drug Sensitivity Biomarkers

P217 Xi Wu, Xu Chen, You Duan, Shengqiang Xu, Nan Cheng, and Ning An, A Study on Gait-based Parkinson’s Disease Detection

P218 S M Ashiqul Islam, Christopher Kearney, and Erich Baker, CSPred: A machine-learning-based compound model to identify the functional activities of biologically-stable toxins.

P219 Dongwon Kang, Jeongwoo Seo, Jinseung Choi, and Gyerae Tack, Fall Prediction Model for the Elderly Using Postural Sway

P220 Juexin Wang, Lyu Zhen, MD Shakhawat Hossain, Gary Stacey, Dong Xu, and Trupti Joshi, SoyTSN: A Web-based Prediction Tool for Soybean Tissue Specific Network within SoyKB

P221 GEERVANI KONETI and NARAYANAN RAMAMURTHI, “Parallelized Variable Selection and Modeling based on Prediction” algorithm on GPU for Feature Selection and ADMET Model Generation

P223 Greg Ostroy, Diana Prieto, Gu Yuwen, Elise Dedoncker, and Rajib Paul, Flu MODELO 1.0:, A Simulation Model and

Graphic Interface for Training and Decision Support for Influenza Management

P224 Pengwei Hu, Keith C.C. Chan, Lun Hu, and Henry Leung, Discovering Second-Order Sub-Structure Associations in

Drug Molecules for Side-Effect Prediction

P225 Yang Liu, Duolin Wang, Juexin Wang, Trupti Joshi, and Dong Xu, Application of Deep Learning in Genomic

Selection

P226 Hakimeh Ameri and Kathryn Cooper, A Compartmental Network Model for the Spread of Whooping Cough

P228 Thanh Thieu, Jonathan Camacho, Pei-Shu Ho, Diane Brandt, Julia Porcino, Denis Newman- Griffis, Ao Yuan, Min

Ding, Lisa Nelson, Elizabeth Rasch, Chunxiao Zhou, Albert Lai, and Leighton Chan, Inductive identification of

functional status information and establishing a gold standard corpus: A case study on the Mobility domain

P229 Matt Spencer, Jacob Gotberg, and Chi-Ren Shyu, Quasi-Palindrome Effects on DNA Sequence Evolution

P230 Sidharth Sen, Mary Galli, Andrea Gallavotti, and Trupti Joshi, DEVELOPMENT OF AN INFORMATICS

ANALYTICS WORKFLOW FOR DAP-SEQ DATA EXPLORATION AND VALIDATION FOR AUXIN RESPONSE

FACTORS IN MAIZE

P231 Saad Khan, Gavin Conant, and Dong Xu, Effects of evolutionary pressure on histone modifications.

P232 Duolin Wang, Dongpeng Liu, Yuexu Jiang, and Dong Xu, MusiteDeep: a Deep-learning Framework for Protein Post-translational Modification Site Prediction

P233 bin xue and Bi zhao, Measuring the Inter-sample Heterogeneity by Dynamic PCA Biplot

P234 GEERVANI KONETI, DIPAYAN GHOSH, and NARAYANAN RAMAMURTHI, Classification Models For

CaCo-2 Permeability Using Chemical Information and Machine Learning Techniques: Scope and Limitations

P236 Trupti Joshi and yuexu Jiang, IMPRes: Integrative MultiOmics Pathway Resolution Algorithm and Tool

P237 Murugesan Raju, Danlu Liu, Frederick Fraunfelder, and Chi-Ren Shyu, Discovering Multifactorial Associations with

the Development of Age-Related Cataract Using Contrast Mining

P239 Jan Jelínek, Petr Škoda, and David Hoksza, Platform for ligand-based virtual screening integration

P240 Rastislav Galvanek and David Hoksza, Template-based prediction of RNA tertiary structure using its predicted secondary structure

P241 Wang Ren Qiu, Chunhui Xu, Xuan Xiao, and Dong Xu, Computational prediction of ubiquitination protein using evolutionary profiles and functional domains

P242 Lingtao Su, Dong Xu, and Guixia Liu, A new method for disease-related gene prioritization

49

P243 Penghui Shang and Dongpeng Liu, A deep-learning framework for amidation site prediction

P244 Sadia Akter, John Bromfield, Katherine Pelch, Angela Meng, Gil Wilshire, Sarah Crowder, Danny Schust, Bret

Barrier, Wade Davis, Trupti Joshi, and Susan Nagel, A Multi-Omics Informatics Approach for Identifying Molecular

Mechanisms and Biomarkers in Clinical Patients with Endometriosis

P245 Ali Foroughi pour and Lori A. Dalton, Optimal Bayesian Feature Filtering for Single-Nucleotide Polymorphism Data

P246 Midusha Shrestha, Bidhan Bhattarai, Marc Pusey, and Ramazan Aygun, Schema Matching and Data Integration on

Protein Crystallization Screens

P247 Timothy Haithcoat and Chi-Ren Shyu, Geospatial Health Context Table

P248 Rebecca Shyu, Timothy Haithcoat, and Mirna Becevic, Spatial Association Mining Between Melanoma Prevalence Rates, Risk Factors, and Healthcare Disparities

P249 Zhen Lyu, Shuai Zeng, and Trupti Joshi, Enabling Precision Medicine with CancerKB and KBCommons Informatics Framework

P250 Siva Ratna Kumari Narisetti, Shuai Zeng, Zhen Lyu, and Trupti Joshi, Development of "KBCommons" - Universal Informatics Framework for Multi-Omics Translational Research

P251 Radoslav Krivák, David Hoksza, and Petr Škoda, Improving quality of ligand-binding site prediction with Bayesian optimization

P252 Asma Ben Abacha, Alba G. Seco de Herrera, Ke Wang, L. Rodney Long, Sameer Antani, and Dina Demner-

Fushman, Named Entity Recognition in Functional Neuroimaging Literature

P254 Sairam Behera, Adam Voshall, Jitender S. Deogun, and Etsuko N. Moriyama, Performance comparison and an ensemble approach of transcriptome assembly

P255 Shuai Zeng, Siva Ratna Kumari Narisetti, Zhen Lyu, and Trupti Joshi, KBCommons: A multi ‘OMICS’ integrative framework for database and informatics tools

P256 Asuda Sharma and Hesham Ali, Analysis of Clustering Algorithms in Biological Networks

P258 Vi Dam and Hesham Ali, On the Integration of Assembly and Non-Assembly Approaches for Comparing Biological

Sequences

P259 Mingchao zhou, Shanshan Ling, Hongxia Chen, and Ruihuan Pan, Inhibition of Notch signaling pathways contribute

to neuroprotection effect by the combination of astragalus membranaceus and ligustrazine in rat model after thrombolysis of cerebral ischaemia

P260 Joshua Herndon and Sumi Singh, Protein Structural Domain Prediction Based on Dihedral and Geometric Angles

P261 Almog Boanos, Anitha Sri Mothukuri, Kaitlin A. Goettsch, and Dhundy K. Bastola, Investigation and Utilization of Personal Food Computers for Research in Drug Development and Biomedicine

P265 Mikhail Kovalenko, Richard Hammer, and Dmitriy Shin, Quantification of Visual Diagnostic Heuristics During Simulated Pathology Diagnosis

50

Conference WiFi Access

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IEEE BIBM 2018 Call for Papers