cambridge healthtech institute’s...beyond genome is a six-day event covering computational tools...

Beyond Genome is a six-day event covering computational tools for analysis and correlation of genomic data, as well as novelproteomic technologies and their applications in drug discovery and development. During the past eleven years, this event hasgrown from a single conference offering into one of the most respected multiconference events on the market. The first two daysare dedicated to In Silico Biology, which explores developing computational tools that translate raw data into workable modelsor simulations, providing guidance for target selection and drug development. Next is the Bioinformatics and Genome Researchportion of the event, focusing on the computational advances necessary to comprehend the vast amount of information gatheredthrough the Human Genome Project. The final portion of this event concentrates on Proteomics, offering in-depth coverage ofnew high-throughput protein profiling technologies and their impact on diagnostic and therapeutic product development.Researchers and executives interested in discovering how these novel approaches to generating and analyzing biological datacan help streamline their R&D process should clear their schedules to attend CHI's Beyond Genome 2002.

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Cambridge Healthtech Institute, 1037 Chestnut Street • Newton Upper Falls, MA 02464tel: 617-630-1300 or toll-free in the U.S. 888-999-6288 • fax: 617-630-1325 • e-mail: [email protected]

Cambridge Healthtech Institute’s

For details or to register on line, visit the official web site: www.beyondgenome.com

Information for the Computational Age

CorporateSponsors:

CorporateSupport:

• Over 10 years of scientific excellence

• Network with over 1,100 attendees

• Full Press Room

• Visit Over 50 Exhibits

• Dual Tracks at Bioinformatics & Proteomics

• Over 75 Presentations at this year’s event

Fourth Annual

IINN SSIILLIICCOO BBIIOOLLOOGGYYJune 2-3, 2002

Eleventh Annual

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June 4-5, 2002

Sixth Annual

PPRROOTTEEOOMMIICCSSJune 6-7, 2002

NEW!

Advances in genomics and proteomics have greatly improved our knowledge of the components of biological systemsat the molecular level. The next logical step is to understand how these components interact in order to model thosebiological systems in silico. This conference will showcase examples and applications of computational modeling of cells,tissues, and disease. Faced with an overabundance of potential targets, such models offer the promise of improved tar-get prioritization compared with relying on empirical research alone. While such models are far from being a completerepresentation of a biological system, examples are already emerging where this method has aided in a greater under-standing of a disease state, as well as target prioritization, and ultimately drug development. Anyone interested in uti-lizing in silico methods as a valuable tool for development of therapeutics strategies should attend this event.

Cambridge Healthtech Institute’s Fourth Annual

IInn SSiilliiccoo BBiioollooggyy:: Modeling Systems Biology for Research and Target PrioritizationJune 2-3, 2002 • Hilton San Diego Resort • San Diego, California

Genomics and proteomics are continuing to ramp up the speed with which new data are generated on expression, struc-ture, interaction, and function. Each of these types of data presents challenges in terms of interpretation, but the biggestchallenge lies in finding better ways to integrate different types of data. This is particularly true as more researchers takea systems biology approach, looking for comprehensive scope. Another huge challenge is to find efficient ways to cutthrough the noise of variability in comprehensive data to focus in on what is most relevant to a specific disease, path-way, or therapeutic target. This conference will focus on the tools needed to systematically link different types of datasets and annotate the experimental data with clinical information.

Cambridge Healthtech Institute’s Eleventh Annual

BBiiooiinnffoorrmmaattiiccss aanndd GGeennoommee RReesseeaarrcchh

June 4-5, 2002 • Hilton San Diego Resort • San Diego, California

The key to obtaining maximum return on investment in genomics is emphasizing strong capabilities in the field of pro-teomics. The high-throughput identification and quantification of protein expression, as well as studies of protein func-tion, bring the researcher closer to the actual biology than studies of gene sequence or gene expression alone. Advancesin analysis of protein-protein interactions and subcellular protein localization, industrializing protein characterization,and novel approaches to determination of protein function pay off by accelerating diagnostic and therapeutic productdevelopment. The Proteomics conference emphasizes the applications of novel and mature protein profiling technolo-gies-including mass spectrometry, yeast two-hybrid, isotope-coded affinity tags, 2-D differential gel electrophoresis, 2-D capillary electrophoresis, and protein microarrays-in discovering disease biomarkers for diagnostic applications andidentifying and validating new targets and disease pathways for drug discovery and development.

Cambridge Healthtech Institute’s Sixth Annual

PPrrootteeoommiiccss ::Applications in Drug Development


For details or to register on line, visit the official web site: www.beyondgenome.com

Sponsoring Publications:

WebPartners

SponsoringSociety:

International Society forComputational Biologywww.iscb.org

SponsoringOrganizations:

Accelrys is the leading provider of software for biologistsand chemists. Our bioinformatics and simulation software

addresses issues ranging from understanding protein structure and function tomanaging and mining genomic data. Our platform technology and consultingservices enable enterprise-wide solutions tailored to today's research organiza-tions. The result is great science, faster.

Applied Genomic Technology Capital Funds (www.agtc-funds.com) is the first specialty venture group focused

exclusively on genomics. Formed by NewcoGen Group, and OneLibertyVentures, AGTC Funds' limited partners include institutional investors, strate-gic corporate partners and individuals. AGTC expects to play a leadership rolein selecting, funding, and developing new genomics-application companies.

BD Biosciences, a business segment of BD (Becton, Dickinsonand Company), has four business units: Clontech, DiscoveryLabware, Immunocytometry Systems, and Pharmingen. Asone of the largest companies supporting the life sciences, BD

Biosciences provides integrated, high-value products and services for genomics,proteomics, drug discovery and development, and cell analysis.

Gene Logic Inc. is a leading genomics-based biocontentand bioinformatics company focused on developing infor-

mation products related to gene activity in human disease and toxicity to opti-mize rapid, reliable and cost-effective pharmaceutical and biotechnologyresearch and development. Through its expertise in biosamples, high-through-put genomics technologies and software development, the Company has devel-oped a series of gene expression information solutions based on its core product,the GeneExpress® Suite.

Lion Bioscience facilitates and accelerates Life ScienceR&D by providing integrated information solutions for dis-

covery. With our proven tools, solutions and advisory services our customers arereaching the cutting edge in the race for the scientific and business success.LION advances the quest for knowledge. We help life science companies address the challenges of modern product develop-ment by providing IT systems for turning data into information, as well as advancedsolutions for refining information into knowledge. Our systems and solutions helpLife Science companies to evaluate biological, chemical, pharmacological, toxico-logical and medical data and information more quickly, more effectively and morecomprehensively. We apply our systems and solutions internally, together withstate-of-the-art high-throughput technologies to fuel the integrated drug discoveryand diagnostics research efforts carried out by our iD³-team.

OGS is a biopharmaceutical company applying integrated proteomicsand genomics for the discovery, development and commercialisation oftherapeutic products. We use our proprietary technologies and bioinfor-matics to identify disease-associated proteins, which are the gateway to

novel treatments and diagnostics.

Omnigon Technologies is a system solutions provider focusedon optimizing and accelerating genomics- and bioinformatics-

based drug discovery. The Company invents solutions to complex, data-intensiveproblems using its Transfinite Representation Theory as a framework. This theory isan innovative mathematical methodology that enables large volumes of data to self-organize into smaller, simpler, and more coherent units to eliminate computationalbottlenecks and increase analytical throughput.

Silicon Genetics is a leader in developing and commer-cializing life science informatics products for high-growthsegments of the life sciences industry, including gene

expression, high throughput screening, and proteomics. Our goal is to provideversatile tools to enable scientists to accelerate their research and drug discoveryefforts. Products include the enterprise wide integrated gene expression analysissolutions, GeneSpring (TM), GeNet (TM), and MetaMine (TM).

Corporate Sponsors:

SCIENTIFIC ADVISORSDr. Igor Goryanin, GlaxoSmithKlineDr. Seth Michelson, Entelos, Inc.Dr. Eric K. Neumann, Beyond Genomics, Inc.Dr. Bernhard O. Palsson, Genomatica, Inc.

SATURDAY, JUNE 14:00- Early Registration6:00pm

SUNDAY, JUNE 2

7:00am Registration and Light Continental Breakfast

NETWORKS8:30 Chairperson's Opening CommentsDr. Tom Paterson, Chief Scientific Officer, Entelos, Inc.

8:40 Explaining Changes In Gene Expression UsingMolecular Interaction Networks

Dr. Trey Ideker, Whitehead Pfizer Computational Biology Fellow, WhiteheadInstitute for Biomedical ResearchIn addition to using gene-expression profiling to differentiate disease statesand identify markers, there has been a recent explosion of interest in com-bining expression profiles with protein interactions, protein and metabolicexpression profiles, and other types of large-scale biological data. Integrationof these complementary data sources may lead to a more fundamental under-standing of the underlying molecular mechanisms that cause a particularexpression profile and, by extension, its associated disease. Along these lines,Dr. Ideker and colleagues have constructed a network of all known molecu-lar interactions in yeast, drawing data from publicly accessible databases ofprotein-protein, protein-DNA, and small-molecule interactions. When inte-grated with gene-expression profiles, this network provides plausible explana-tions (and testable hypotheses) for the interactions regulating the observedexpression changes. After describing these methods, Dr. Ideker will provide ademonstration of Cytoscape, a publicly-availablesoftwarepackage developedin his group to display and analyze integrated network models of this type.Application to the yeast galactose-utilization pathway is shown.

9:10 Elucidating the Inherent Generic Logic of theBehavior of Cellular Networks

Dr. Zoltan N. Oltvai, Department of Pathology, Northwestern UniversityMedical SchoolOne of the most important goals of postgenomic biology is the elucidation of thefundamental logic and constraints that determine the systemic behavior of a cell ormicroorganism. In their totality, the combined interaction of various cellular con-stituents form a complex cellular network, whose functional organization ultimate-ly determines all cellular behavior. Our research aims to understand the organiza-tion of this networks from various perspectives, with a combination of experimen-tal and theoretical approaches. In our recent work we have demonstrated that thelarge scale organization of metabolic-, and protein interaction networks appearidentical in all species, all possessing a robust and error tolerant scale-free topolo-gy. We then also showed that the uncovered topology represents a very strong con-straint on the evolutionary capacity of all organisms. In my talk, I would focus on

our new work on the refinement of the uncovered network topology and on theframework by which regulatory interactions in eukaryotic cells are organized.

9:40 Next-Generation Drug Target Prioritization viaData-Driven Computer Simulation of MammalianCell Cycle Control and Colon Cancer

Dr. Colin C. Hill, Chief Executive Officer, President, Gene Network Sciences, Inc.Major advances in genomics, proteomics, and cellular and molecular biology havelead to a proliferation of biological databases without yielding an understandingof the integrated function and behavior of biochemical networks and the cellularresponses which they control. Our goal is the systematic integration of diversebiological data types into computer simulations of the dynamics of mRNA andprotein concentrations in response to various growth factors and hormones andother external stimuli and internal perturbations (i.e. knockouts). The GeneNetwork Sciences (GNS) approach combines the forward predictive approach ofmathematical and computer modeling with the inferential approach of data-min-ing and bioinformatics to create the most comprehensive cellular simulations ofhuman disease. Using the Diagrammatic Cell Language™, GNS has created thelargest known network of interconnected signal transduction pathways and geneexpression networks controlling human cell growth.

10:10 Refreshment Break

10:50 A Network Genomic Analysis of Microbial GenomesDr. Christian Forst, Los Alamos National LaboratoryWith the advent of post-genomic research and the exponentially growing numberof completely sequenced genomes comes a driving need and opportunity for the useof multi-leveled computational approaches that combine genome information withnon-genomic network connections. At the lowest level of molecular organizationindividual cellular components are formed, often by assembly of multiple polypep-tides, and at a higher level, set of cellular components group into cellular networks.Context information induced by cellular networks combined with genomic contextare powerful approaches in prediction of new functional features and high levelanalysis, such as network inferrence. I will present recent developments and novelapproaches that take into account network information and generic context infor-mation. Special emphasis is laid on gene-expression analysis in connection withinferred cellular networks as well as references to relationships between gene-con-text/operon structure and networks are made. For this purpose conventionalsequence comparison and phylogenetic analysis of individual sequences has beenextended to cellular networks. A method has been developed that combines distanceinformation of aligned sequences with network information of cellular Genomicsanalysis has been performed on a variety of metabolic networks. By comparative net-work genomics of pathogenic organisms with non-pathogenic relatives networksthat play a role in virulence of pathogens are identified.

11:20 Feature Extraction from Short and NoisyBiological Time Series

Dr. Andras Aszodi, Head, Computational Biology and Chemistry Group,Novartis Research InstituteGene expression time series obtained from microarray experiments are short andnoisy, making quantitative analysis difficult. In order to obtain at least a qualita-tive description, characteristic features of the time series were extracted by statis-tical techniques, and were encoded in an intuitive string representation. Timeseries that shared the same description string could thus be clustered together,facilitating the identification of co-regulated groups of genes.

11:50 Panel DiscussionThe session will close with a question-and-answer panel, which will provide anopportunity to interact and review your issues with the speakers.

Cambridge Healthtech Institute’s Fourth Annual

IInn SSiilliiccoo BBiioollooggyy:: Modeling Systems Biology for Research

and Target PrioritizationJune 2-3, 2002 • Hilton San Diego Resort • San Diego, California

12:00-5:00pm Exhibit Setup

12:20 Lunch (provided by Cambridge Healthtech Institute)

SYSTEMS MODELING

2:00 Chairperson's CommentsDr. Adam Muzikant, Director of Modeling Sciences, Physiome Sciences, Inc.

2:05 Using The Entelos Diabetes PhysioLab ToImprove Clinical Trial Design and Data Analysis

Dr. Camille J. Wallwork, Medical Fellow, Department of Medical Informatics,Johnson & Johnson Pharmaceutical R & D We have been using the Entelos Diabetes PhysioLab to simulate a treatment fortype 2 diabetes. In spite of starting with only preclinical data for this compound,new insights were obtained for clinical trial design using this top-down biosimu-lation of human insulin and glucose metabolism. We are currently receivinghuman data, and the model is assisting in the pharmacodynamic analysis and fur-ther tuning of upcoming clinical trials for this compound.

2:35 BioSystematics: Discovery through AppliedSystems Biology

Dr. Eric K. Neumann, Vice President, Bioinformatics, BeyondGenomics, Inc.The life sciences are at a very unique point in time where both science and technolo-gy have both advanced to a new level of analytical depth and throughput. With thecompletion of the Human Genome Project, researchers are poised to begin the nextphase of elucidating how living systems function. This will involve identifying howgenes function and how their products interact with other molecules, within the con-text of processes and their assumed roles. This places new demands for representingand handling new forms of complex information, including pathway and causal mod-els in biology. The annotations and testing of such models in all likelihood will requirethe use of knowledge representations (ontologies) for the biological sciences, whichcan link to large volumes of diverse experimental data. Beyond Genomics is develop-ing a systems biology approach for integrating and analyzing information from multi-ple platforms that we call BioSystematics™. It integrates three parallel data producingplatforms: MS/MS proteomics, MS/NMR metabolomics, and microarray transcrip-tomics. This forms the input for our BioSystematics™ Knowledge Repository forSystems Biology, which enables us to build causal and dynamic models for normal anddiseased systems, capturing not only sequence/structural information, but alsoprocess-oriented information relevant to biochemical systems. The knowledge derivedfrom our research will be relevant to many aspects of drug discovery.

3:05 Towards Quantitative Validation of Immune-System Models: Germinal Center Dynamics dur-ing the Responses to 2-phenyl-5-oxazolone and(4-hydroxy-3-nitrophenyl)acetyl

Dr. Steven Kleinstein, Computer Science, Princeton UniversityNumerous in vivo and in vitro studies have elucidated the basic molecular mechanismsthat underlie many aspects of immune response dynamics. However, in most cases itis not well understood how these mechanisms fit together. This is particularly true forthe germinal center reaction (an important component of the immune response).Although many models of the germinal center have been proposed, most only attemptto explain the high-level, qualitative behavior of the system. Our work demonstratesthat such a methodology can be misleading and presents a number of contributionstoward the development of detailed, quantitative models of the germinal center reac-tion. In this talk, I will review progress towards the next generation of detailed, com-prehensive and validated models of the germinal center. This will include my recentproposal concerning the source of the key mutant paradox in the germinal center, aswell as new methods to estimate the hypermutation rate directly from clonal tree data(which depict the ancestral relationships between cells). Finally, I will discuss thenecessity of using discrete and stochastic models versus differential equations.

3:35 Refreshment Break

4:15 Towards the Automated Generation ofInflammation Pathway Hypotheses fromExperimental Data and Prior Knowledge

Dr. Rick Stanton, Senior Research Automation Engineer, Amgen Inc.Increased pathway knowledge can guide advancement of the most important thera-peutic targets as well as aid in the early identification of potential therapeutics des-tined to succeed or fail due to side effects. Initial efforts towards the automated gen-eration of inflammation pathway hypotheses will be presented. Efforts prototyped

with Oracle, Java, and Matlab include (1) database knowledge capture and visuali-zation; (2) algorithmic interpretation of prior knowledge within a rule set; (3) acomparison of Bayesian, maximum likelihood, and mutual information techniqueson an inflammation pathway example—combining microarray data with priorknowledge; and (4) modeling gene expression with difference equations.

4:45 In Silico Multicellular Biology and GenomicsDr. Eric Werner, President, Cellnomica, Inc.There have been a number of attempts to simulate living cells in software (e-cell, T7,Physiome). There have also been efforts to simulate chemical interactions in organs,as well as simulations of neural nets. Others have simulated cellular interactionsbased on physical relationships such as adhesion. However, none of those attemptssimulate the actual dynamic development of multicellular structures such as tissueand organs. We report on results achieved by researchers at Cellnomica, Inc., work-ing on the simulation of multicellular development as well as other multicellularprocesses such cell signaling and chemical gradients. More specifically, we show thatnew insights can be gained into the nature, organization and function of genomeswhen looked at from the perspective of the role of genomes in multicellular devel-opment of tissue and organs. Many diseases such as cancer are inherently multicel-lular phenomena. Our research shows that perhaps the best way to understand suchdiseases is by way of simulations that take into account not just genes or the inter-actions of genes, but the entire process of how networks of genes function togeth-er in cells to engender the disease phenotype. The cure for diseases such as cancercan be more probable with the kind of understanding and control that multicellularsimulation can give. Other areas that may gain from the simulation of multicellulargenome guided processes are cloning, stem cell research, tissue engineering, drugdelivery modeling, and nanotechnology, to name a few.


5:45 Close of Day One

MONDAY, JUNE 3

8:15- Poster and Exhibit Viewing and Light Continental8:45 Breakfast

CELL MODELING

8:45 Chairperson's CommentsDr. Igor Goryanin, Head, Cellular Simulations and Pathway Modelling,GlaxoSmithKline

8:50 Bioengineering Systems Approach toCue/Signal/Response Analysis of Cell DecisionProcesses

Dr. Douglas A. Lauffenburger, Professor of Bioengineering & ChemicalEngineering, Massachusetts Institute of Technology Physiological functions of cells from higher organisms are governed by cues fromtheir extracellular environments, via transduction into intracellular signals thatregulate biochemical and biophysical processes underlying phenotypic controlmechanisms. A current challenge is to develop approaches to understanding andcontrolling these signaling and response networks. We are employing a bioengi-neering systems approach, emphasizing a combination of quantitative measure-ment, modeling, and manipulation in integrative manner, toward addressingexample problems in cell migration, death/survival, and differentiation.

9:20 The Virtual Cell ProjectDr. Les Loew, Professor of Physiology, and Director, Center for BiomedicalImaging Technology, University of Connecticut Health CenterThe Virtual Cell is a modular computational framework that permits constructionof models, application of numerical solvers to perform simulations, and analysis ofsimulation results. A key feature of the Virtual Cell is that it permits the incorpo-ration of realistic experimental geometries within full 3D spatial models. The sys-tem is designed for cell biologists to aid both the interpretation and the planningof experiments. This talk will describe the status of the project illustrated with sev-eral applications to cell biological problems.

9:50 Molecular Ontology for Cellular SignalingDr. Shankar Subramaniam, Adjunct Professor, Salk Institute for BiologicalStudies, University of California, San Diego Cellular signaling phenomena is the hallmark of nearly every cellular event. Amajor challenge of the post-genome sequence era is the mapping of signalingpathways which will then provide a detailed picture of the sequence of molecularevents that lead to a cellular response. The first step towards this mapping is thecharacterization of the "states" of a signaling molecule along with all the proteininteractions and the molecular function. The vast amount of experimental dataavailable today is unfortunately not structured to allow such "state" characteriza-tion. This talk will outline an ontology for the signaling molecules that will leadto a precise definition of a signaling pathway.

10:20 Poster and Exhibit Viewing, Refreshment Break

11:00 From Intracellular Signal Transduction toCellular Organization

Dr. Birgit Schoeberl, Division of Bioengineering & Environmental Health,Massachusetts Institute of TechnologyEGF plays a central role during embryonic and postnatal development as well as intumor progression. However, the cell response seems to be strongly affected bythe mode of representation of the growth factor, e.g., matrix-bound versus dif-fusible modes. Starting off with a mathematical model describing the dynamics ofthe EGF induced signaling we attempt to build the bridge between intracellularsignaling and cellular organizations. Therefore we use an hybrid approach consist-ing of a dynamical model for the signal transduction based on ODEs and discretemodel for the cellular organization based on the concept of cellular automata.

11:30 Mathematical Modeling of Entire Organisms andWhole Cells

Dr. Igor GoryaninWhat is the whole cell modelling (WCM)? Why do we need WCM? What can wedo with whole cell models? What is the potential difficulties and challenges forWCM? Examples of whole cell models, E.coli model development at GSK, andpharmaceutical applications of WCM will be discussed.


12:30 Lunch (on your own)

TARGET PRIORITIZATION AND DRUGDEVELOPMENT

2:00 Chairperson's CommentsDr. Les Loew

2:05 Ways Computational Biology of Function MightImpact on Drug Discovery: Early Lessons fromthe Alpha Project at TMSI

Dr. Roger Brent, Vice President, The Molecular Sciences InstituteIn biology, prediction can operationally define understanding. That is, if a scien-tist can predict the future behavior of a biological system given knowledge of itscurrent state, then we might assert that the scientist understands the system.Here, I will talk about the Alpha project. This is an effort to understand, (in theabove narrow sense) a particular signal transduction pathway in yeast. This path-way governs the response of the organism to mating pheromone. Alpha is anambitious effort, requiring us and others to devise new wet lab experimentalmethods. It also requires us to develop computational frameworks that allow usto "compute on" qualitative and quantitative experimental information. I willdescribe some findings from the front lines of this project and suggest how suc-cess in it might change current paradigms governing drug discovery and therapy.

2:35 Mathematical Modeling of Diseases, Drugs, andTargets

Dr. Frank Tobin, Director, Scientific Computing and Mathematical Modeling,GlaxoSmithKlineThis talk will describe how mathematical approaches can be used to model dis-eases, pathways, and target opportunities. such models span a broad range of con-ceptual granularity from phenomenological approaches to disease mechanisms or

detailed mechanistic models of pathways or chemical reactions. Examples willincluded blood coagulation and osteoporosis and, when appropriate, an indica-tion of how receptor kinetics can become a starting point to building larger andmore sophisticated models of a disease.

3:05 Gaining Insights Into Drug Targets andCandidates Using Biological Simulations

Dr. Ramprasad Ramakrishna, Senior Modeling Scientist, Physiome Sciences, Inc.Physiome Sciences recently launched its PathwayPrism(tm) platform, whichenables scientists to map, model and simulate biochemical pathways and integrategene and protein expression data. The platform's knowledge and data annotationfeatures also allow users to create a supporting reference base for models. Scientistscan use the platform to test hypotheses and generate new insights into the behav-ior of signaling pathways, which will be demonstrated through case studies.


4:05 Virtual Patients: The Ultimate "System" forTesting Clinical Relevance In Silico

Dr. Tom PatersonIn Silico Biology has moved beyond the proof-of-concept phase. From targetidentification and validation to optimizing lead compounds and improvingpatient selection in clinical trials, applications have advanced compounds througheach phase of the drug discovery and development pipeline. We now stand at theforefront of enabling high-throughput in silico predictions that are both clinicallyrelevant and robust. The opportunity is at hand to change the drug developmentparadigm from one in which millions of pharma-dollars are chasing "potential"targets that will prove non-efficacious to one in which researchers create and testintegrated hypotheses in an array of Virtual Patients in a comprehensive, high-throughput biological and physiological system. Entelos has pioneered the use ofVirtual Patients to enable research to be driven by hypotheses testing rather thandata crunching. Leaping over correlation-based analyses, Virtual Patients encap-sulate the pharma-partners' proprietary knowledge into a predictive frameworkfrom which to drive streamlined empirical research.

4:35 Application of In-Silico Biology Technology InClinical Development and It's Challenges

Dr. Hung-Ir Li, Research Scientist, Eli Lilly and Company In-silico biology technology has advanced and gained increasing attentions fromthe industry in the past few years. Yet, most of the applications seemed to be inthe discovery phase helping to identify, validate, and prioritize targets.Applications in the clinical development sector to further enhance the overallR&D productivity and the associated challenges will be discussed.

5:05 From Gene Expression to PathwayCharacterization: Speeding Up Prioritization ofDisease Targets

Dr. Christos Hatzis, Vice President, Technology, Silico Insights, Inc.Systems biology offers a promising approach to furthering our understanding ofbiological systems by synthesizing the information that is quickly becoming avail-able at different levels of biological organization, including genomic DNA,mRNA, protein, post-translational modifications, protein interactions, pathways,and disease networks. Yet, ascertaining the function of proteins from incomplete-ly characterized genes still remains a fundamental problem in biology and a keystep towards achieving the goals of systems biology. In this paper, we address theproblem of integrating prior knowledge on genes and their products with exper-imental measurements of gene expression and post-translational modifications toelucidate gene function and pathway membership.

5:35 Panel DiscussionThe session will close with a question-and-answer panel, which will provide anopportunity to interact and review your issues with the speakers

6:05 Bayside Reception, Held Jointly withBioinformatics

7:30 Close of the In Silico Biology Conference

Scientific AdvisorsMr. Thomas Downey, Partek Inc.Dr. A. Keith Dunker, Washington State UniversityDr. Eric Fairfield, Fairfield EnterprisesDr. Terry Gaasterland, Rockefeller UniversityDr. Hwa Lim, D'Trends Inc.Dr. Stephen Sharp, Iobion InformaticsDr. Jonathan Sheldon, Confirmant Ltd.Dr. John N. Weinstein, National Cancer Institute, NIH

Keynote PresentationsDr. Tim Hunkapillar, President and Chief Scientific Officer, Discovery BiosciencesProf. Klaus Lindpaintner, Vice President and Director, Roche Genetics, F.Hoffmann-La Roche AG

SpeakersDr. David Balaban, Signature BioScienceDr. Cory Brouwer, CuraGen CorporationDr. Celeste Brown, Washington State UniversityDr. Jake Chen, Affymetrix, Inc.Dr. Robert J. Deans, Plexus Vaccine Inc.Dr. A. Keith Dunker, Washington State UniversityDr. Adam Godzik, The Burnham Institute and San Diego Structural Genomics CenterDr. Itay Gat, Compugen Ltd.Dr. Joshua Harr, Linux NetworXDr. Sui Huang, Children's Hospital/Harvard Medical SchoolDr. Joanne K. Kelleher, George Washington University Medical Center andMassachusetts Institute of TechnologyDr. Les Klimczak, Psychiatric Genomics, Inc.Dr. Irwin J. Kurland, University of California, Los AngelesDr. Michael Liebman, University of Pennsylvania and ProSanos, Inc.Dr. Nikolas Maniatis, University of SouthamptonDr. Marc Marti-Renom, Rockefeller UniversityDr. John Morrison, AstraZeneca Pharmaceuticals Dr. Zoran Obradovic, Temple UniversityDr. Anna R. Panchenko, National Center for Biotechnology InformationDr. Christopher V. Rao, Lawrence Berkeley National LaboratoryDr. George Rose, Johns Hopkins University School of Medicine Dr. Burkardt Rost, Columbia UniversityDr. Alan H. Roter, Iconix Pharmaceuticals, Inc. Dr. Eric Rubin, Harvard School of Public HealthDr. Jonathan Sheldon, Confirmant Ltd.Dr. Mark Swindells, InpharmaticaDr. Adel M. Talaat, University of Texas Southwestern Medical CenterProf. Shoshana J. Wodak, Université Libre de Bruxelles and EuropeanBioinformatics InstituteDr. Peter Wright, Scripps Research InstituteDr. Ying Xu, Oak Ridge National LaboratoryDr. Fuminori Yamaguchi, Lynx Therapeutics Inc.Dr. Lisa Yan, Accelrys Inc.Dr. Qing Yan, MedImmune, Inc.Dr. Bo Yuan, The Ohio State UniversityDr. Robert J. Zagursky, Wyeth Lederle Vaccines

PLENARY SESSIONClinical Applications of BioinformaticsUnderstanding, Diagnosing, and Treating Common Complex DiseaseGenomics and Informatics in Drug DevelopmentUnderstanding Pathways from a Clinical PerspectiveAnalysis of Disease and Drug SignaturesIdentification of Genomic Amplifications and Deletions in Cancer CellsIntegrated Chemogenomics Information System for Lead Prioritization

CONCURRENT TRACK 1Networks and Metabolic PathwaysGenomewide Approach to Emergent Cell BehaviorManaging Signaling Pathway InformationGene Expression to Measure Networks and Protein CompleasesUnraveling the Structure of Biochemical Regulatory NetworksDatabase of Molecular Interactions and ProcessesLinking Genomics to Function via Metabolic PhenotypingEvaluating the Metabolic Significance of Single Gene Deletions

CONCURRENT TRACK 2Data-Modeling Tools for Mining the Genome for DiscoveriesComplete Assembly, Functional Analysis, and Sequence Comparison of theHuman and the Mouse GenomesFinding the Best Strategy for Sequence Profiles ComparisonFirst Linkage Disequilibrium Maps: Delineation of Block StructureNew Framework for Biological Data ClusteringMultipole Coupling SpectroscopyIdentifying and Visualizing Interactions on a Genomic ScaleOvercoming the Complexities Associated with Managing Linux Clusters

CONCURRENT TRACK 1Protein DisorderUnstructured Proteins, Coupled Folding, and Binding TransitionsProtein DisorderData Mining for Estimating Commonness of Protein DisorderEvolutionary Characteristics of Disordered ProteinsIntrinsic Disorder in Cell-Signaling and Cancer-Associated Proteins

CONCURRENT TRACK 2Vaccine DevelopmentExperimental Genomics of VirulenceStructurally Informed Approach to Vaccine Epitope SelectionPotential Bacterial Vaccine Candidates Using BioinformaticsData Integration in Comparative Genomics for Viral Vaccine DiscoveryCutting Edge Vaccine Development

Plenary SessionProtein FunctionIntegrated High-Throughput Protein AnalysisProteins Not PredictionsProtein Structure and Function for Entire ProteomesProtein Structure Modeling for Structural GenomicsFrom Fold Recognition to Function PredictionDrug Target Selection Using Structural Information and the Human GenomeUsing Solvation Model with Implicit Membrane for GPCR Structure Modeling

Cambridge Healthtech Institute’s Eleventh Annual

BBiiooiinnffoorrmmaattiiccss aanndd GGeennoommee RReesseeaarrcchh


Corporate Support:

MONDAY, JUNE 34:00- Early Registration6:00pm

6:00- Opening Reception (held jointly with In Silico7:30pm Biology)

6:30- Poster and Exhibit Set-up8:30

TUESDAY, JUNE 47:30am Registration, Poster and Exhibit Viewing, and

Light Continental Breakfast

PLENARY SESSIONCLINICAL APPLICATIONS OF

BIOINFORMATICS8:30 Chairperson's RemarksDr. Jonathan Sheldon, Chief Technology Officer, Confirmant Ltd.

8:40 Keynote Presentation

Understanding, Diagnosing, and Treating CommonComplex Disease: Opportunities and Challenges forGenetics and GenomicsProf. Klaus Lindpaintner, Vice President, Research and Head, Roche Geneticsand Roche Center for Medical Genomics, F. Hoffmann-La Roche, Ltd

9:15 Genomics and Informatics in Drug DevelopmentDr. John F. J. Morrison, Head, Global Clinical Genomics, AstraZenecaPharmaceuticals This talk will discuss where genomics, proteomics and informatics has been suc-cessful in the reclassification of disease, the identification of prognostic markersand biomarkers of disease activity, and the response to therapy.

9:45 Understanding Pathways from a Clinical PerspectiveDr. Michael Liebman, Director, Computational Biology; Professor, CancerBiology; and Investigator, Abramson Family Cancer Research Institute,University of Pennsylvania; and ProSanos, Inc.The use of systems engineering approaches, e.g., stochastic network models, enablesus to represent, analyze, and simulate the behavior of complex pathways in biology.We have previously applied this approach to complex systems to analyze geneexpression data, drug target validation, and therapeutic dosing levels. Our currentemphasis is on the ability to simulate physiological characteristics related to defininga molecular phenotype, using polymorphism data, and coordinating this with "land-mark" analysis to evaluate the contribution of underlying mechanisms to normaland abnormal physiology. The application of this to the aging of the female repro-ductive system and its impact on individualized disease risk will be presented.

10:15 Refreshment Break, Poster & Exhibit Viewing

11:00 Combining Chemo- and Bioinformatics forAnalysis of Disease and Drug Signatures inPsychiatric Disorders

Dr. Les Klimczak, Director, Bioinformatics and Information Technologies,Psychiatric Genomics, Inc.Toward our goal of understanding the genes and genetic pathways associated

with various psychiatric diseases, Psychiatric Genomics is comparing changes ofgene expression profiles between healthy and diseased brain tissues to those elicit-ed in cultured neuronal cells or in vivo rat model systems by therapeutically effec-tive psychiatric drugs. In contrast with the traditional approach of pursuing a sin-gle target for a given disease treatment, we are identifying sets of altered genesthat will represent disease or drug "signatures." We use these signatures in ourmultiparameter high-throughput screening, MPHTSSM, to find novel small mol-ecule compounds that are able to elicit gene expression changes that are similarto the drug signatures and complementary to the disease signatures. We will dis-cuss expression changes associated with schizophrenia and bipolar disorder, aswell as rodents and cultured human neurons challenged with the antibipolarmedication valproic acid, as examples of our drug development strategies.

11:30 Identification of Genomic Amplifications andDeletions in Cancer Cells

Dr. Fuminori Yamaguchi, Senior Scientist, Department of Molecular Biology,Lynx Therapeutics Inc.We have developed a high-resolution technique (>150,000 markers) to identifyamplified and deleted chromosomal regions in cancer cells. Differentially fluores-cent-labeled probes are prepared from cancer and normal cell line DNAs that arecompetitively hybridized to human genomic DNA fragments mounted onmicrobeads. Beads that have fluorescent ratios that differ from 1:1 are isolatedand the DNA sequences associated with these beads determined. Deletions in theY chromosome and an amplification of X chromosome were detected when anonsmall cell lung cancer cell line was compared to DNA from normal lympho-cytes prepared from the same individual.

12:00 An Integrated Chemogenomics InformationSystem for Lead Prioritization

Dr. Alan H. Roter, Vice President, Informatics, Iconix Pharmaceuticals, Inc. The use of genomics technologies, such as DNA microarrays, provides a new classof information that medicinal chemists and toxicologists can use to predict poten-tial toxicity and efficacy. This information can be used to prioritize leads for opti-mization. Integration of chemical and genomic data with chemoinformatics andbioinformatics tools enables researchers to query across diverse data domains tofind relationships and build hypotheses. We have created a reference database thatincorporates extensive experimental and curated data and provides an integratedenvironment that incorporates data relating to chemical structures, genes, bioas-says, and DNA microarrays. This DrugMatrix™ system provides information onknown toxicities and efficacies as molecular signals in the genome.

12:30 Sub Classification Of Drugs: Combining MedicalRecords And Genotypic Information

Dr. Itay Gat, Senior Scientist, Computational Medicine, New ResearchDirections, Compugen Ltd.For many years, physicians as well as researchers have observed significant varia-tions in the response of different patients to the same drug. A better understand-ing of these variations requires that we address the phenotype, genotype and envi-ronmental aspects of patients' sub populations. In order to overcome the hurdlesinvolved in the collection of large genetic pools, we utilize large databases ofmedical records. This enables us, in the second stage, to focus on relatively smallnumbers of genotypic samples using sophisticated bioinformatic tools. The talkwill present several examples of the possible re-positioning of drugs in the mar-ket based on our innovative methods.

1:00 Luncheon

CONCURRENT TRACK 1NETWORKS AND METABOLIC

PATHWAYS

2:15 Chairperson's CommentsDr. Terry Gaasterland, Assistant Professor, Rockefeller University

CONCURRENT TRACK 2DATA MODELING TOOLS FOR MINING

THE GENOME FOR DISCOVERIES2:15 Chairperson's CommentsMr. Thomas Downey, President, Partek, Inc.

2:20 To Decipher the Book of Life: Complete Assembly,Functional Analysis, and Sequence Comparison ofthe Human and the Mouse Genomes

Dr. Bo Yuan, Division of Human Cancer Genetics, The Ohio State UniversityThe human genome draft provides a unified basis for describing genomic structureand function. A similar draft for mouse genome has been recently assembled using awhole genome shotgun approach. Both drafts are sufficiently accurate to provide use-ful annotation, enabling direct observations of previously inferred biological phe-nomena. We report here functionally annotated human and mouse gene indicesplaced directly on their genomes. The indices are based on the integration of publictranscript, protein, and mapping information, supplemented with human-mousewhole genome comparison and computational prediction. Comparative sequenceanalysis also provided confirmatory evidence for transcripts and identified exons, reg-ulatory elements, and candidate genes that were missed by other methods. Wedescribe numerous global features of the human genome and examine the syntenicrelationship with the mouse. Initial sequence analysis reveals highly varied genomicplasticity and ordered chromosomal landscapes associated with paralogous gene clus-ters and distinct functional compartments. These annotation data were synthesized toproduce observations of gene density and number that accord well with historicalestimates. We estimate that both genomes contain 60,000 to 70,000 transcriptionalunits, with exon sequences comprising 4%. The creation of a comprehensive geneindex requires the synthesis of all available computational and experimental evidence.

2:50 Finding the Best Strategy for Sequence ProfilesComparison

Dr. Anna R. Panchenko, Staff Scientist, National Center for BiotechnologyInformation, NIHDue to the genome-sequencing efforts many proteins are now characterized onlyby sequence, with no experimental identification of their three-dimensional struc-ture or function. Methods comparing the sequence to the library of profiles rep-resenting the known protein families have proven recently to be a useful tool forrecognition of divergent protein family members. Another approach to increasethe recognition sensitivity is to explore the sequence space in the vicinity of asequence with unknown properties and to develop methods of profile-profile com-parison. We are going to present a new method of aligning two sequence profileswith each other and investigate the factors influencing the overall performance ofprofiles in the database search. It has been shown that the developed profile-pro-file search method yields higher recognition sensitivity compared to sequence-pro-file methods and produces more accurate three-dimensional models, which allowsthe correct annotation of functional sites.

3:20 The First Linkage Disequilibrium Maps:Delineation of Block Structure

Dr. Nikolas Maniatis, Senior Member, Genetic Epidemiology, School ofMedicine, Human Genetics Division, University of SouthamptonLinkage Disequilibrium (LD) provides information for positional cloning and the studyof evolution and different populations. We will present theory and application of amethod to construct and LD map in which map distances are additive and populationspecific maps are expected to be approximately proportional. LD maps so constructedare analogous to the linkage map that has proven invaluable in genome studies to date.LD maps offer much higher resolution, however, and demonstrate that certain genomeregions show a distinct "block" structure of plateaus, perhaps corresponding to regionsof low haplotype diversity, and steps representing recombination events or recombina-tion hot-spots. Unlike the recent "haplotype map" proposal, for which haplotypes arepopulation specific, a standard LD map may be useful for all populations that we antic-ipate will show similar patterns, but not magnitude, of LD.

3:50 A New Framework for Biological Data ClusteringDr. Ying Xu, Senior Staff Scientist and Group Leader, Protein InformaticsGroup, Oak Ridge National LaboratoryWe have recently developed a new computational framework for biological data cluster-ing. In this framework, a multidimensional data set is represented as a minimum span-ning tree, a concept from the graph theory. We have rigorously proved that a cluster inthe data set is always represented as a subtree of the minimum spanning representing thedata set. Hence a multidimensional data-clustering problem can be solved as a tree-par-titioning problem. The simplicity of a tree structure facilitates efficient implementationof sophisticated clustering algorithms, which are otherwise computationally intractable.We have also demonstrated that the spanning tree-based clustering algorithms are high-ly tolerant to noise and are highly effective for clustering problems with extremely com-plex cluster boundaries, which cause problems to many existing clustering algorithms.We have applied this to a number of biological data analysis problems, including microar-

2:20 Genomic Regulatory Networks: From TopologySpace to Phase Space—A GenomewideApproach to Emergent Cell Behavior

Dr. Sui Huang, Instructor, Surgical Research, Children's Hospital/HarvardMedical SchoolAfter the identification of the partial list of genes and proteins, the next step ingenomics is the identification of their interactions that establish a network.However, determination of the genome's wiring diagram itself is of limited usefor understanding the dynamics of living systems at the phenotype level. Basedon simulations of idealized, generic network models and experimental data ofcell fate regulation, it is now argued that cellular phenotype can be understoodas phase singularities of high-dimensional network dynamics. Fundamentalproperties of regulatory networks that follow from the model, such as thecoexistence of stability and flexibility, are presented, and their implication forcell regulation, multiple-target drug action, and tumorigenesis are discussed.

2:50 Managing Signaling Pathway InformationDr. Jake Chen, Bioinformatics Computer Scientist, Affymetrix, Inc.Today, the bulk of pathway information is either buried within biological litera-ture or left unanalyzed in raw microarray data format. In this talk, I will describethe challenges of collecting, representing, and analyzing metabolic/signalingpathway data. I will present our ongoing research using advanced database tech-niques to extract, model, and apply our knowledge on pathways. I will showexamples of how the pathway information, when integrated with other geneannotation data, leads to successful interpretation of expression microarray data.

3:20 Using Gene Expression to Measure Networksand Protein Complexes

Dr. Terry GaasterlandGene expression data imposed on known metabolic pathways and molecularcomplexes indicates which components are critically regulated, which areubiquitously present, and which are regulated in common with components ofother known pathways or complexes. Correlation of gene expression data andprotein protein interaction data indicates the degree to which gene expressioncan be used to discover unknown pathways or pathway extensions. TheCluster Explorer module of the TANGO (Transcriptome Analysis ofGenomes) system computes, visualizes and calculates the significance of pro-tein-protein relationships in gene expression clusters.

3:50 Unraveling the Structure of BiochemicalRegulatory Networks

Dr. Christopher V. Rao, Physical Biosciences, Lawrence Berkeley NationalLaboratoryBacterial chemotaxis has emerged as a model system for analyzing the propertiesof biochemical networks. An intriguing aspect of many intracellular networks isrobustness; in chemotaxis, sensory adaptation weakly depends on the concentra-tion and activity of the individual proteins that compose the pathway. Instead,the structure of the network gives rise to sensory adaptation. Gross descriptionsof this structure, such as scale-free behavior, are consistent with properties suchas robustness but do not address either function or mechanism. With the goal ofidentifying a set of principles governing sensory adaptation, we develop a quan-titative model of the chemotaxis pathway in Bacillus subtilis, a pathway that func-tions the same as the enteric paradigm yet is organized differently, as evidentthrough genetics and biochemistry. This alternative model required that wedeconstruct the enteric model of chemotaxis in the context of identifying com-mon principles governing both networks. We argue that comparative analysis isnecessary to identify universal principles coordinating network behavior and pro-vide insight into the evolutionary divergence of these two networks.


5:00 Representing and Analyzing BiologicalFunction with aMAZE, a Database ofMolecular Interactions and Processes

Prof. Shoshana J. Wodak, Unité de Conformation de MacromoleculesBiologique, Université Libre de Bruxelles; and EMBL Outstation, EuropeanBioinformatics InstituteDetermining the biological function of a myriad of genes, as well as under-

Cambridge Healthtech Institute, 1037 Chestnut Street • Newton Upper Falls, MA 02464tel: 617-630-1300 or toll-free in the U.S. 888-999-6288 • fax: 617-630-1325 • e-mail: [email protected]

ray gene expression data analysis, regulatory binding site identification, and two-hybriddata analysis.


5:00 Identifying and Visualizing Protein-ProteinInteractions on a Genomic Scale

Dr. Cory Brouwer, Project Leader, PathCalling, Bioinformatics, CuraGen CorporationKnowledge of how proteins interact is important to understanding cell processes andthe roles proteins and drugs play in the cell. CuraGen uses PathCalling®, our high-throughput yeast two-hybrid system, to identify protein-protein interactions both forspecific disease or drug-related genes and for whole genomes. The PathCalling softwareis an important part of CuraGen's integrated bioinformatics platform, GeneScape®. Wehave developed a visualization scheme that shows cellular localization, disease associa-tion, gene expression information, and possible cross-species homologs in a singlegenomic-scale protein-protein interaction map. This global view of the interaction mapcomplements the gene-based interaction views and enables discoveries that might havebeen missed using solely a gene-based approach to querying the data.

5:30 Multipole Coupling SpectroscopyDr. David Balaban, Vice President, Informatics and Computational Biology,Signature BioScienceMultipole coupling spectroscopy (MCS) is a new form of microwave spectroscopy thatmeasures soft vibrations of large molecules in a natural aqueous environment. The even-tual goal at Signature is to create data management systems to organize and mine thenew measurements for proteins and to build relationships to traditional measurementssuch as X-ray crystallographic structures. This talk will describe the strategy and statusfor building and using these systems.

6:00 Overcoming the Complexities Associated withManaging Linux Clusters

Dr. Joshua Harr, Chief Technical Officer, Linux NetworXLinux clusters have become the high-performance compute (HPC) engine of choice forbioinformatic organizations involved in the analysis and correlation of genomic data thatare seeking raw number crunching power with greater flexibility, reliability, scalability,and price/performance over traditional supercomputers. Early adopters of the technolo-gy viewed the task of setting up an efficient and powerful Linux cluster system as a chal-lenge and typically have had access to a dedicated administration staff to ensure clusterstability. Linux clustering continues to move into new HPC markets and is also chalkingup successful installations in various high-availability (HA) and bioinformatics environ-ments. In today's competitive environment, organizations must focus on their core com-petencies instead of spending valuable resources integrating, configuring, and managingsuch systems. This being the case, cluster management is a top issue concerning thefuture adoption of the technology. As cluster systems scale from dozens to hundreds andeven to thousands of processors, management becomes exponentially complex,and canbe a daunting challenge for any organization. Keeping software up to date, monitoringhardware and software status, and even performing routine maintenance require signifi-cant effort. To alleviate these efforts, administrators need to identify cluster managementtools to help them gain control of cluster administration. The goal of any organizationand administrator is to dedicate resources to applications—not system management.


standing how they interact to yield a living cell, is the major challenge of the post-genome-sequencing era. The complexity of biological systems is such that thiscannot be envisaged without the help of powerful computer systems capable ofrepresenting and analyzing the intricate networks of physical and functional inter-actions between the different cellular components. Here we present the aMAZEdatabase, which constitutes an effort in this direction. Its data model embodiesgeneral rules for associating molecules and interactions into large complex net-works that can be analyzed using graph theory methods. It deals with a large vari-ety of processes, including metabolic pathways, protein-protein interactions, generegulation, transport, and signal transduction. These processes are mapped intotheir spatial localization. The ability of representing simultaneously several func-tional classifications is also provided. A distinct feature of aMAZE is its object-ori-ented, modular, and open user interface, the aMAZE Framework. Using theframework, queries are invoked through dedicated modules; data can be linked toexternal sources, interactively browsed, and transferred between modules; andnew modules can be readily added. In addition to typical queries, available mod-ules currently include a custom-built Diagram Editor for the automatic layout,display, and interactive modification of pathway diagrams. The framework alsofeatures procedures for analyzing network graphs, as well as specialized tools forpathway annotation. Systems like aMAZE should help the biologists in under-standing, analyzing, and ultimately modeling complex cellular networks.

5:30 Linking Genomics to Function via MetabolicPhenotyping

Dr. Joanne K. Kelleher, Research Professor, Department of Physiology, GeorgeWashington University Medical Center; and Visiting Scientist, Department ofChemical Engineering, Massachusetts Institute of TechnologyMetabolic phenotyping requires information about the metabolic map of the cell,levels of metabolites, and the flux rates of pathways. Two additional tools refinethis information: Isotopomer Spectral Analysis, a 13C labeling technique, pro-vides estimates of fluxes of various metabolites into a common intermediatepools. Metabolic Control Analysis describes the quantitative role of each enzymein the map in determining the fluxes. To develop a systems biology approach tomammalian cell metabolism we link metabolic phenotype data with DNAmicroarray data.

6:00 Functional Genomics: Use of 13C-MassIsotopomer Distribution Analysis to Evaluate theMetabolic Significance of Single Gene Deletions

Dr. Irwin J. Kurland, Assistant Professor of Medicine and Member, MolecularBiology Institute, University of California, Los AngelesWhile the genome projects have produced information regarding interestinggenes for study, the metabolic phenotype of single gene deletions may turn outto perturb complex in vivo flux interactions in ways that cannot be predicted. Useof 13C-mass Isotopomer Distribution Analysis will be described for the elucida-tion of complex metabolic phenotypes resulting from single gene knockouts.


CONCURRENT TRACK 1PROTEIN DISORDER

8:30 Chairperson's CommentsDr. A. Keith Dunker, Professor, Biochemistry/Biophysics, School of MolecularBiosciences, Washington State University

8:35 Intrinsically Unstructured Proteins and CoupledFolding and Binding Transitions

Dr. Peter Wright, Professor, Department of Molecular Biology, ScrippsResearch InstituteA significant proportion of gene sequences appears to code not for folded glob-ular proteins but for proteins that are intrinsically unstructured. Such proteinsfrequently participate in important regulatory functions in the cell, often under-going folding transitions upon binding to their cellular targets. NMR is unique

CONCURRENT TRACK 2VACCINE DEVELOPMENT

8:30 Chairperson's CommentsDr. Robert J. Zagursky, Distinguished Research Scientist and Group Leader,Biotechnology/Bioinformatics Discovery Research, Wyeth Lederle Vaccines

8:35 Experimental Genomics of Virulence: Treasurefrom TraSH

Dr. Eric Rubin, Assistant Professor of Immunology and Infectious Diseases,Department of Immunology and Infectious Diseases, Harvard School of PublicHealthMutagenesis has been the mainstay of bacterial genetic investigations.Transposon site hybridization (TraSH) couples transposon mutagenesis withDNA microarray analysis to identify genes required for survival on a genomewide

WEDNESDAY, JUNE 58:00am Poster and Exhibit Viewing and Light Continental Breakfast

in being able to provide detailed insights into the conformational preferences ofunfolded and partly folded proteins as well as characterize the folding processesthat mediate their physiological functions.

9:05 Protein DisorderDr. George Rose, Professor, Department of Biophysics and BiophysicalChemistry, Johns Hopkins University School of MedicineWhat is the nature of conformational space for an unfolded protein? Is it a randomcoil, as assumed in much earlier work, or does it have underlying order, as found insome recent studies? Specifically, the energy landscape for a random coil is a temper-ature-independent "egg-crate," featureless and devoid of structural information. Isthis a valid description for an unfolded protein? To address this question, we exploreconformational space for a simple polyalanine model system under the influence of asoft-sphere repulsive force and find that the classical alanine dipeptide has a pro-nounced temperature dependence. For an alanine seven-mer, the landscape isordered, and the equilibrium population is largely distributed within just two steri-cally favored pockets. Each pocket corresponds to spontaneous fluctuations arounda noncooperative helix; the larger one is a canonical, left-handed polyproline II helix.

9:35 Data Mining for Estimating Commonness ofProtein Disorder and Understanding TheirFlavors

Dr. Zoran Obradovic, Director, Center for Information Science and Technology,and Professor, Computer and Information Sciences, Temple UniversityWe will first describe an algorithm for classification from a sample with a biasedclass distribution followed by its application to estimating commonness of pro-tein disorder (proteins with long regions lacking a fixed structure in the nativestate). We will also report on a supervised algorithm for detecting and charac-terizing different types of protein disorder. The algorithm is based on a compe-tition among protein disorder predictors for individual disordered proteins. Thenumber of competing predictors, starting from a single one, is incrementallyincreased allowing their specialization for different types of disorder. An applica-tion of this algorithm followed by an extensive statistical and qualitative evalua-tion of the obtained partitioning provided strong evidence that (i) there are atleast three distinct flavors of protein disorder; (ii) all three flavors are commonin nature, but the flavor statistics are very different among 32 genomes; and (iii)different disorder flavors are dominant in bacteria, archaea, and eukaryotes.


10:45 Evolutionary Characteristics of IntrinsicallyDisordered Protein

Dr. Celeste Brown, Adjunct Assistant Professor, School of MolecularBiosciences, Washington State UniversityFamilies of proteins having regions that form ensembles rather than single struc-tures (i.e., regions of intrinsic disorder) have been subjected to two analyses: (1)estimation of the patterns of amino acid substitutions and (2) comparison of theevolutionary rates of ordered and disordered parts within the same protein. Oneof the most fundamental steps in bioinformatics is to align two or moresequences. Scoring matrices for amino acid sequence alignments are based pri-marily on fully folded, ordered proteins, but here we explore the developmentof a matrix adjusted to disordered regions. An iterative algorithm of realigningsequences and recalculating matrices will be presented. Results indicate animproved ability to detect and discriminate related disordered proteins. Thisimprovement relates to an altered pattern of amino acid substitutions comparedto ordered protein. To compare the evolutionary rates of ordered and disorderedregions within the same proteins, pair-wise genetic distances were determinedseparately for each type of region for families having at least one member with astructurally-characterized region of disorder of 30 or more consecutive residues.For five families, there were no significant differences in pair-wise genetic dis-tances between ordered and disordered sequences. The disordered regionevolved significantly faster for 19 of 26 families, and the ordered region evolvedfaster in two families. No factor could be found to predict whether a disorderedregion would evolve faster or slower than the ordered regions of the same pro-tein. Although disordered regions in general evolve faster than ordered regionsperhaps because of reduced structural constraints, more work is needed tounderstand the underlying causes of the exceptions to this general trend.

11:15 Intrinsic Disorder in Cell-Signaling and Cancer-Associated Proteins

Dr. A. Keith DunkerRational and structure-based drug design depends on a protein having a specif-ic 3-D structure. Native proteins, however, are often intrinsically unfolded or

scale. Using this method we have performed comprehensive identifications ofgenes required by Mycobacterium tuberculosis to grow during model infection.Mutations in these genes produce attenuated strains that could serve as possibletuberculosis vaccines.

9:05 A Structurally Informed Approach to VaccineEpitope Selection

Dr. Robert J. Deans, Vice President of Research and Development, PlexusVaccine Inc.

Computational biology and structural homology modeling can be appliedto the selection of vaccine epitopes. Next-generation neural net algorithmsfor the prediction of T-cell epitopes can provide rapid and accurate epitopecandidates from full pathogen genomes. In humoral vaccine development,bioinformatics input of genetic variation and functional annotation can becombined with structural homology modeling tools to identify target epi-topes in molecules. Both strategies allow the rapid design of vaccines thateliminate the biological risk posed when using attenuated microbes or tox-ins.

9:35 The Identification of Potential Bacterial VaccineCandidates Using Bioinformatics

Dr. Robert J. ZagurskyBioinformatics tools are currently being used to predict potential protein-basedvaccine candidates from pathogenic bacterial genomes. Our framework for pre-dicting vaccine candidates is based on using various algorithms to mine genomicsequences and includes the incorporation of actual protein data from proteomics.The bulk of vaccine research currently under way utilizes bacteria cultured in alaboratory setting. One caveat to this approach is whether we might be missingimportant in vivo expressed protein antigens. Are there ways to improve our pre-diction methods and narrow our choices to rapidly screen through the hundredsof putative proteins predicted from a single bacterial genome?


10:45 Data Integration in Comparative Genomics forViral Vaccine Discovery

Dr. Qing Yan, MedImmune, Inc.Genome comparison is an important approach in the identification of viral vac-cine candidates. Different viral strains can be compared at genomic and pro-teomic levels. Structural-function analysis and comparison of the strains may helpus find potential vaccine targets. The studies such as homology search in openreading frames (ORFs), motif analysis, and comparison of polymorphisms in viralgenomes involve various types and large amounts of data. I will discuss our deci-sion to support strategies for the integration of these data in comparativegenomics for viral vaccine candidate discovery.

11:15 Cutting-Edge Vaccine Development: ADGEProfiling

Dr. Adel M. Talaat, Center for Biomedical Inventions, Department of InternalMedicine, University of Texas Southwestern Medical CenterDNA microarrays have evolved to be the standard technology for measuring geneexpressions on a genomewide scale. We adapted the Array technology forDifferential Genomewide Expression (ADGE) profiling in living hosts. As proofof principle, we used the mouse model for ADGE profiling to identify genes ofMycobacterium tuberculosis that are expressed in vivo. All gene expression levelswere clustered using different algorithms (hierarchical and self-organizing maps),which are currently tested as vaccine candidates.

11:45 Panel Discussion


PLENARY SESSIONPROTEIN FUNCTION

1:30 Chairperson's RemarksDr. Eric R. Fairfield, President and Chief Executive Officer, Fairfield Enterprises

1:40 Keynote PresentationIntegrated High-Throughput Protein AnalysisDr. Tim Hunkapillar, President and Chief Scientific Officer, Discovery Biosciences

2:15 Proteins Not PredictionsDr. Jonathan SheldonFor the full medical value inherent in the DNA sequence of the human genometo be realized, the logical next step is to define those regions of the genome thatencode functional proteins. Computational methods for gene prediction are farfrom perfect, resulting in whole genes or exons being missed or wrongly predict-ed by these complex algorithms. For this reason, the goal of unambiguously iden-tifying all protein-coding genes in the genome is most likely to be achieved byexperimentally determining the amino acid sequence of naturally expressed pro-teins by direct mass spectrometric analysis. An overview describing the mappingof this protein sequence information to the publicly available annotated versionof the human genome will be presented. This integrated approach gives a uniqueprotein centric view of the human genome and unprecedented insight intogenome organization, gene fine structure, and alternative splicing.

2:45 Protein Structure and Function for EntireProteomes

Dr. Burkardt Rost, Associate Professor, Biochemistry & Molecular BiophysicsDepartment, Columbia UniversityMore than 60 organisms have been entirely sequenced. We confirmed that eukary-otes have relatively more long proteins than prokaryotes and archaes and that theoverall amino acid composition is similar among the three. While we predicted thatabout 15-30% of all proteins contained transmembrane helices in each of the threekingdoms, we found coiled-coil proteins and proteins with long regions lacking reg-ular secondary structure remarkably more present in eukaryotes. For about 10-40%of all proteins we can infer structure; on the other hand structural genomics willhave to target the white spaces for about half of all proteins. For eukaryotes alone,we estimate the number of carefully chosen targets to exceed 18,000.


3:45 Protein Structure Modeling for StructuralGenomics

Dr. Marc Marti-Renom, Laboratory of Molecular Biophysics, Pels FamilyCenter for Biochemistry and Structural Biology, Rockefeller UniversityThe shapes of most protein sequences will be modeled based on their similarityto experimentally determined protein structures. The current role, limitations,challenges, and prospects for protein structure modeling are discussed in the con-text of structural genomics.

4:15 From Fold Recognition to Function Predictionto Target Selection for Structural Genomics

Dr. Adam Godzik, Associate Professor and Program Director, Bioinformaticsand Biological Complexity Program, The Burnham Institute; and BioinformaticsCore Leader, Joint Center for Structural Genomics, San Diego SupercomputerCenter, University of California, San DiegoAn automated protocol to annotate large groups of proteins with predicted struc-tural and functional information was developed on the basis of a profile-profile fold

recognition algorithm FFAS, enhanced by several tools for modeling, active siteanalysis (SITE), and surface features analysis (SurfMap). General overview of theprediction protocol and several examples of how specific predictions were followedfrom a computer lab to the laboratory bench will be presented. The same protocolis also used to identify crystallization targets for the San Diego-based Joint Centerfor Structural Genomics (JCSG). JCSG is a joint project between UCSD, Scripps,and SLAC to develop a high-throughput crystallography pipeline, focusing on solv-ing structures of representative sets of C. elegans proteins. The overall structure andpreliminary results of JCSG will be reviewed and discussed.

4:45 Drug Target Selection Using StructuralInformation and the Human Genome

Dr. Mark Swindells, Chief Scientific Officer, InpharmaticaIn spite of numerous advances in biological, screening, and chemical technologiesthe rate of discovery of new medicines against novel protein targets remains poor.Only a small proportion of the human genome is now thought likely to code fordrug target proteins, due to the restrictive requirements imposed on a proteinsinvolvement in a disease pathway (biological validity) and ability to bind a suit-able small-molecule (druggability) that must be met. The approaches being takenat Inpharmatica to genome-scale structure-based annotation of proteins, facilitatethe evaluation of druggability and the molecular annotation of proteins on com-mon pathways. Examples of both the construction and use of the InpharmaticasBiopendium resource will be presented.

5:15 Using Solvation Model with Implicit Membranefor GPCR Structure Modeling

Dr. Lisa Yan, Senior Manager, Protein Engineering, Accelrys Inc.Current estimate indicates that more than 50% of the drugs on the market are tar-geting GPCR proteins. However, it is very difficult to determine the GPCR struc-tures using an experimental method. To date, only two 7-helical transmembraneproteins have known structure in the public database. Modeling of GPCR is impor-tant but very difficult due to the limitation of the theoretical models available. Wedeveloped a novel method that uses the extension of the Generalized Born modelwith implicit membrane, GBSA/IM, to model GPCR structures. Simulation resultsof transmembrane proteins are in good agreement with experimental results. Amini-pipeline to predict the GPCR structure based on homology modeling and thesimulation using our solvation model will be discussed.

5:45 Reception/Beach Party, Held Jointly withProteomics

7:00 Close of Bioinformatics and Genome ResearchConference

disordered. Anecdotal observations suggest that cell-signaling proteins are rich in such disordered regions. Application of predictors of intrinsic disorder to variousgenomes spanning the three kingdoms of life indicated a large jump in intrinsic disorder for the eukaryotes, perhaps reflecting a greater use of disordered proteins forsignaling and regulation in organisms with nucleated cells. To further test for an association between signaling and disorder, four protein databases were analyzed. Theresults indicated substantially more intrinsic disorder in cancer-associated and signaling proteins as compared to two control sets, thus reinforcing the importance ofintrinsic disorder in signal transduction. These results have important consequences for drug design and discovery. Combining and integrating bio- and chemoinfor-matics promise to open new doors in the drug discovery process, from the identification of novel targets and elucidation of their functions to the discovery and devel-opment of lead compounds with desired properties. As these tools are generally applied, however, bio- and chemoinformatics approaches ignore intrinsically disor-dered protein. At the very least, current and improved predictors could identify disordered regions that are very unlikely either to crystallize or to bind drug mole-cules by the traditional lock-and-key mechanisms; such information could be extremely useful at the early stages of target selection. In the longer term, combiningprediction of intrinsic disorder with other information will recommend alternative strategies for protein characterization. The ultimate goal will be to develop newstrategies for finding drug molecules that target intrinsically disordered proteins and thereby alter signaling pathways in useful ways.

11:45 Panel Discussion 12:15 Lunch (on your own)

Scientific AdvisorsDr. William Hancock, ThermoFinniganDr. Joshua LaBaer, Harvard Medical SchoolDr. Scott D. Patterson, Celera Genomics CorporationDr. John Yates, The Scripps Research Institute

Keynote AddressDr. Sam Hanash, University of Michigan Medical Center and HUPOPresident

SpeakersDr. Dave Anderson, Rigel Inc.Dr. Kevin P. Baker, Human Genome Sciences, Inc.Dr. Maribel Beaumont, DNAX Research, Inc.Dr. John Bergeron, Caprion Pharmaceuticals, Inc.Dr. Walter Blackstock, Cellzome AGDr. John S. Chant, CuraGen Corp.Dr. Thomas P. Conrads, National Cancer InstituteDr. Pat Griffin, Merck Research LaboratoriesDr. Timothy J. Griffin, Institute for Systems BiologyDr. Timothy A.J. Haystead, Duke University and Serenex, Inc.Dr. Steve Holmes, Oxford GlycoSciences Dr. Shen Hu, University of WashingtonDr. Ian Humphery-Smith, Glaucus ProteomicsDr. Stephen F. Kingsmore, Molecular Staging, Inc.Dr. David Lockhart, Ambit BiosciencesDr. Gregg B. Morin, MDS ProteomicsDr. Jens Niewoehner, Xerion Pharmaceuticals AGDr. Scott D. Patterson, Celera Genomics Corp.Dr. Emanuel F. Petricoin, U.S. Food and Drug AdministrationDr. Keith Rose, GeneProt Inc.Dr. Walter Schubert, MelTec GmbHProf. Stefan Ståhl, Affibody ABDr. Raymond Stevens, The Scripps Research Institute and Syrrx, Inc.Prof. A. Donny Strosberg, HybrigenicsDr. Michael A. Tainsky, Wayne State UniversityDr. Steven Taylor, MitoKorDr. Robert G. Urban, ZYCOS, Inc.Dr. Jan van Oostrum, Novartis Pharma AGDr. Peter Wagner, Zyomyx, Inc.Dr. John E. Wiktorowicz, Lynx TherapeuticsDr. John R. Yates, The Scripps Research Institute

Keynote AddressDefining the Components of a Global Human Proteome Initiative

High-Throughput ProteomicsIndustrial-Scale ProteomicsStructural Proteomics in Drug Discovery

Integrated Approach to Pathway DiscoveryHigh-Throughput Mass Spectrometry

Concurrent Track 1Protein-Protein InteractionsProtein Complex AssemblyTarget ValidationProtein Interaction Mapping by MS

Concurrent Track 1Subcellular LocalizationIntegral Membrane Protein DiscoveryMitochondrial Proteome MappingQuantifying the Topological Proteome

Concurrent Track 2Functional ProteomicsICAT and MS to Determine Differential ExpressionDrug Target Discovery and ValidationAffinity Reporter LigandsEpisomal Expression VectorsFunctional Proteome Fractionation™Target Discovery by Protein Interaction Mapping

Concurrent Track 1Protein ProfilingComprehensive Proteomic Analysis of Cells and TissuesPhosphoproteome Analysis2-D DIGE in Surrogate Marker Identification2-D Capillary Electrophoresis for Single Cell AnalysisLiquid-Based (Nongel) 2-D Electrophoresis

Concurrent Track 2Protein Microarrays and BiomarkersAntibody Arrays in Pharmacoproteomics New Protein MicroarraysDiscovery of Clinical Trial BiomarkersEpitomics: Analysis of Immune System Response for Cancer DiagnosticsInformatics-Based Mining of Serum Proteomic Patterns

Proteomics Applications: Drug Discovery andDevelopmentMolecular Profiling in Drug DiscoveryFunctional Genomics and ProteomicsPhage Display-Based ScreeningDeveloping Protein TherapeuticsDiscovery of Therapeutic Antibodies

Cambridge Healthtech Institute’s Sixth Annual

PPrrootteeoommiiccss Applications in Drug Development


CorporateSponsors:

HIGH-THROUGHPUT PROTEOMICS

8:30 Chairperson's Opening CommentsDr. Scott D. Patterson, Vice President, Proteomics, Celera Genomics Corp.

8:40 Keynote AddressDefining the Components of a Global HumanProteome Initiative

Dr. Sam Hanash, University of Michigan Medical Center and HUPO PresidentWe have entered the planning phase for major proteome initiatives. There is aneed in this phase to engage in technology and resource development, as well aspiloting and feasibility studies. Ongoing related activities and issues, includingresource mobilization, will be reviewed.

9:15 Proteomics on an Industrial ScaleDr. Keith Rose, Chief Scientific Officer, GeneProt Inc.At GeneProt, by industrial-scale proteomics we refer to the analysis of large num-bers of protein fractions from a pair of samples (e.g., diseased and control) ratherthan the more superficial analysis of very many samples from individuals. We havedeveloped processes applicable to the analysis by mass spectrometry of small pro-teins and of large proteins, by both MALDI and electrospray ionization tech-niques. Small proteins are analyzed by nongel techniques, while larger proteinsare separated by gel-based techniques prior to mass spectrometry. After carefulevaluation, many interesting candidate proteins are synthesized for bioassay.

9:45 High-Throughput Structural ProteomicsAccelerates Drug Discovery

Dr. Raymond Stevens, Professor, The Scripps Research Institute; and Co-founder, Syrrx Inc.First-generation use of the fully integrated structural proteomics technology atSyrrx has started producing its first set of large-scale results. These data are now

progressing into the drug discovery phase where close coupling of virtual ligandscreening, biophysical screening, and co-crystal structures is critical for accelerat-ing drug discovery. Technology and results will be presented that outline thegene-to-drug process.


11:00 Integrating Genomic, Proteomic, andComputational Biology Approaches toDiscovering Novel Proteins and BiochemicalPathways

Dr. John S. Chant, Group Leader, Proteomics, CuraGen Corp.The integration of industrialized yeast two-hybrid technology with expressionanalysis and computational biology is a powerful method for determining disreg-ulation at different points within biochemical pathways. We will discuss the appli-cation of this integrated approach to the discovery of novel interactions andpotential drug targets within disease pathways that may contribute to the onsetof significant diseases.

11:30 High-Efficiency Proteomics UsingChromatograph-Mass Spectrometry

Dr. Scott D. PattersonWe are utilizing targeted chromatography-mass spectrometry (LC-MS) basedapproaches in the search for diagnostic markers and therapeutic targets in specif-ic diseases. Specific classes of proteins are captured and analyzed at the peptidelevel following tryptic digestion, thus allowing LC-MS for quantitation andMS/MS for identification (the latter using the new ABI 4700 proteomics ana-lyzer). Examples of this strategy will be presented.



TRACK 1PROTEIN-PROTEIN INTERACTIONS

1:45 Chairperson's CommentsDr. Walter Blackstock, Vice President, Technology, Cellzome AG

1:50 A Large-Scale Map of Protein Complexes in S.Cerevisae and Its Relevance to Human Biology

Dr. Walter BlackstockAlmost all drug targets are proteins, yet our understanding of the cellular con-text in which proteins operate is surprisingly limited. Few proteins function inisolation, most operating as part of cellular machines comprising multiproteincomplexes. Protein complexes are more than the sum of binary protein-proteininteractions, and as part of the goal of a detailed understanding of protein com-

TRACK 2FUNCTIONAL PROTEOMICS

1:45 Chairperson's CommentsProf. A. Donny Strosberg, President and Chief Executive Officer, Hybrigenics

1:50 Mass Spectrometry and Proteomics: Tools forInvestigating Protein Function

Dr. Timothy J. Griffin, Associate Researcher, Institute for Systems BiologyRecently a core, integrated methodology for the quantitative profiling of proteinexpression has been developed that includes chemical labeling of proteins using iso-tope-coded affinity tag (ICAT™) reagents, multidimensional chromatographic sep-arations, and analysis by tandem mass spectrometry with automated sequence data-base searching. This powerful approach has enabled the investigation of gene

WEDNESDAY, JUNE 55:00- Early Registration and Poster and Exhibit Set-up7:00pm5:45- Reception/Beach Party, Held Jointly with Bioinformatics7:00pm

THURSDAY, JUNE 67:30am Registration, Poster and Exhibit Viewing, and Light Continental Breakfast

7:30- Antibody Microarrays as a New Proteomics Tool8:10Antibody microarray technology as a proteomics tool for profiling protein levels in biological samples is presented. Majorfeatures are direct dual color labeling of biological samples and fluorescent detection of their binding to 400 monoclon-al antibodies. A novel algorithm to compensate for differences in chemical reactivity and chip to chip variability is imple-mented. This is a highly scalable system that may emerge as a fundamental tool for cell biology and proteomics research.

PLENARY SESSION

Sponsored by:

plex assembly in man, we have completed the first large-scale characterization ofprotein complexes in S. cerevisiae.

2:20 Using Proteomics to Identify and ValidatePharmaceutical Targets

Dr. Gregg B. Morin, Vice President, Biology, MDS ProteomicsThe application of proteomic technologies and genomic data to disease-relevanthuman cells and tissues has the potential to discover and validate new proteins andprotein families as therapeutic targets suitable for drug development. By optimiz-ing a co-immunoprecipitation and mass spectrometry-based approach, we havecompleted a short-term pilot project that documented protein interactions span-ning approximately one-quarter of the yeast proteome. MDS Proteomics is apply-ing this approach directly to human cells, along with other technologies we havedeveloped, to discover and validate novel pharmaceutical targets within thehuman proteome.

2:50 A Proteomics Approach to FunctionalGenomics: Mass Spectrometry-Based Mappingof Cellular Protein Interactors of FunctionalPeptides Derived from Retroviral Peptide LibraryCellular Screens

Dr. Dave Anderson, Director, Protein Science and Proteomics, Rigel Inc.Using retrovirally delivered peptide libraries and a screen for cell cycle inhibitors,we have identified peptides that cause cell cycle arrest in A549 human lung car-cinoma cells. Synthetic biotinylated analogs of these peptide affinity-extract setsof interacting proteins not present in extracts were obtained using biotinylatedinactive mutant peptides. With the use of multiple mass spectrometry method-ologies, Western blotting, and the Oracle-8-based proteomics workstationMEDUSA, we have identified and confirmed a number of these proteins. Theresults suggest that more than one protein complex or sets of functional proteinsmay interact with the active peptides and suggest possible mechanisms for cellcycle arrest in these tumor cells.



SUBCELLULAR LOCALIZATION

4:30 Chairperson's CommentsDr. John Bergeron, Chief Scientific Officer, Proteomics, CaprionPharmaceuticals, Inc.

4:35 Proteomics-Based Discovery of Novel SurfaceIntegral Membrane Proteins of Tumor Cells

Dr. John BergeronCaprion applies CellCarta, its proprietary subcellular proteomics discovery plat-form, to create comprehensive intracellular maps identifying the location, ori-entation, and movement of human proteins. Protein maps of functional com-partments within normal and diseased cells are compared to uncover the bio-chemical basis of disease, which leads to the identification of high-quality, bio-logically relevant targets and insights to accelerate drug development. TheCaco-2 cell line is a model for colon cancer representing several of the morpho-logical and biochemical features of transformed colonic epithelial cells. A suiteof proprietary and fully automated technologies that encompass unique cell frac-tionation techniques with high-throughput protein separation, mass spectrom-etry, and bioinformatics has been used to characterize proteins of the surface ofCaco-2 cells. Novel cell surface proteins undetectable by current approacheswere identified by an organelle proteomics approach and represent new poten-tial drug targets relevant to the treatment of colon cancer.

5:05 Mapping the Human Mitochondrial ProteomeDr. Steven Taylor, Scientist, MitoKorIn contrast to the formidable task of mapping entire proteomes of higher organ-isms, or even selected vertebrate tissue, subcellular organelles present a seeming-ly lesser challenge. We have undertaken a major effort to identify and annotate the1,000 to 2,000 proteins estimated to constitute the mitochondrial proteome,"the mitoproteome." Evidence mounts that mitochondrial dysfunction is associ-ated with many degenerative and metabolic diseases; this proteomic resource aidsus in the discovery of novel molecular targets and in finding protein biomarkersof disease.

expression at a magnitude and speed that was once impossible using traditional two-dimensional gel electrophoresis-based methodologies. We are currently developinga next-generation ICAT™ reagent-based approach that employs a MALDI quadru-pole mass spectrometer and novel software tools that enable rapid and selectiveidentification of those proteins that show differential expression levels in the systembeing investigated. This abundance-dependent identification approach promises toincrease not only the throughput of these analyses but also the number of biologi-cally important proteins that are identified; it also provides a powerful and elegantapproach to the analysis of protein complexes isolated by co-immunoprecipitation.

2:20 Validating Protein Targets Using XCALIburDr. Jens Niewoehner, Senior Scientist, Xerion Pharmaceuticals AGOver 90% of the validated drug targets are proteins. Most target validation tech-nologies such as antisense, RNAi, and gene-knockout technologies that are cur-rently used do not act at the protein level; thus the results cannot be readilyextrapolated to protein function. XCALIbur is a target validation technology thatefficiently acts at the protein level and mimics the action of most drugs.XCALIbur is high throughput and can be used to validate targets derived frommicroarray, in silico analysis, or differential protein expression profiles. It can alsobe used for discovery of targets.

2:50 High-Throughput Proteomics: Analysis ofHuman Chromosome 21

Prof. Stefan Ståhl, Chief Scientific Officer, Affibody ABA new high-throughput proteomics strategy based on the production of reporter lig-ands (affinity reagents) will be presented. The approach has been used for functionalanalysis of the 225 putative gene products predicted from the genome sequence ofhuman chromosome 21. Bioinformatics has been used to select Protein EpitopeSignature Tags (PrEST) for each gene locus, and the PrESTs have been expressed,purified, and used to generate specific affinity purified antibodies. The generated affin-ity reagents have been used as reporter ligands for functional analysis of the gene prod-ucts, including expression profiling in different organs using a tissue array. It has beenshown that the reporter ligand proteomics approach can be used for high-throughputstudies of subcellular localization of the various gene products in different tissues aswell as analysis of protein size variations possibly caused by alternative splicing.


4:15 High-Throughput Protein Profiling Coupled withmRNA-Based Expression Profiling andEpisomal Expression Vectors to Validate Targets

Dr. Robert G. Urban, ZYCOS, Inc.Automated workstations have been developed to collect high-throughput proteinexpression profiles. Using an integration of front-end sample processing, two distinctclasses of proteolytic peptides are generated prior to MS/MS-derived sequence analy-sis. The first class is produced via an in vivo proteolytic process. This sample set is high-ly enriched for low abundance and/or high turnover proteins. The second set of sam-ples is derived from in vitro digestion of fractions representing proteins within specif-ic cellular compartments. Collectively, the total data set represents a large portion ofthe expressed proteins. Data derived from mRNA, either in the form of microarray orqRT-PCR, are then used as a tool to rapidly expand expression-related information ona particular lead. The anatomical mapping of gene usage and a quantitative assessmentof the levels of expression between normal and diseased tissues are used to prioritizetargets for validation. The validation of target genes encoding potential pharmaceuti-cal products routinely involves the production and re-administration of an encodedprotein into an animal model. During these efforts the production, purification, andvalidation of the protein product become a significant bottleneck to high-throughputvalidation. To relieve some of these constraints, episomal vectors and polymer-basedgene delivery chemistries have been developed that allow the validation process tobegin without the production of recombinant protein. The DNA formulations arethen tested in animal disease models during which efficacy and/or preclinical safetyparameters are scored. The process flow and required technologies from initial targetdiscovery to validation and then into clinical testing will be presented.

4:45 Mining the Proteome to Discover New Drugsand Their Therapeutic Targets en Masse

Dr. Timothy A.J. Haystead, Professor, Duke University; and Chief ScientificOfficer, Serenex, Inc.Serenex's technology simplifies and rationalizes the study of proteins, both as thera-peutic targets and in their interaction with drug candidates. By combining protein iso-lation and functional analysis with high-throughput drug discovery, Serenex'sFunctional Proteome Fractionation™ (FPF™) and Proteome Mining™ technologiesprovide a powerful, high-throughput method for simultaneous drug and target identi-

fication. Using FPF, sub-proteomes that interact with a common natural ligand such asATP can be captured through a functional interaction with the immobilized ligand onan affinity separations matrix. Serenex has focused its initial efforts on those proteinsthat interact with ATP, which include kinases, dehydrogenases, metabolic enzymes, andstress proteins. Proteome mining is the exposure of the captured sub-proteome todrugs or druglike compounds from a library to identify both new therapeutic candi-dates and their relevant molecular targets. Specificity, biological relevance, and thepotential sources of toxicity for each compound are revealed through these screeningtechnologies. The technologies can be applied to heterogeneous and complex proteinmixtures, such as those derived from a whole animal or human tissue source, withouttime-consuming sample preparation. This significantly increases the likelihood of find-ing all relevant proteins, including unstable but important drug targets. This talk willdescribe examples of how the Serenex technology has been used to identify the molec-ular targets of drugs or druglike compounds from chemical libraries, from preclinicaland clinical development candidates, and from drugs that are on the market.

5:15 Functional Proteomics for Validation of DrugTargets

Prof. A. Donny StrosbergHybrigenics identifies and validates therapeutic targets to improve the efficiency ofthe drug discovery process. The company's approach is based on a high-throughputprotein interaction mapping technology to unravel the role of proteins in functionalpathways, a computer-aided expert analysis platform to prioritize prevalidated thera-peutic targets, and a unique cellular assay to validate the target's functional role, usingthe domains involved in the interacting proteins.



5:35 Protein Fingerprints: Leveraging the CellularProtein Code for Drug Discovery andDevelopment

Dr. Walter Schubert, Chief Executive Officer, MelTec GmbHMelTec uses its whole cell robotic imaging technology, MELK, to visualize andquantify the topological proteome at the single cell level. In this way, the com-pany is able to directly capture information on the protein networks in cellularand subcellular compartments in situ and correlate it with cellular function. Thispositions MelTec to affect and enhance all phases of drug discovery includingdrug targeting and lead optimization, the creation of cellular assays, diagnostics,surrogate markers, and mode-of-action studies. Using MELK, scientists atMelTec were able to characterize proteins specific to certain cancer cells andidentify what could be the first protein marker for ALS.



FRIDAY, JUNE 7

8:00am Poster and Exhibit Viewing and Light Continental Breakfast

TRACK 1PROTEIN PROFILING

9:00 Chairperson's CommentsDr. John R. Yates, Department of Cell Biology, The Scripps Research Institute

9:05 Liquid-Based (Nongel) Two-DimensionalElectrophoresis: The Best of Both Worlds

Dr. John E. Wiktorowicz, Director of Proteomics, Lynx TherapeuticsTwo-dimensional electrophoresis remains the highest resolving separation sys-tem for the visualization of complex mixtures of proteins and for differentialanalyses of reference and target cell extracts. Its use, however, in the pursuit offundamental biological knowledge and the search for therapeutic targets is lim-ited by a number of deficiencies, not the least of which is its inability to (1) con-trol for artifactual qualitative and quantitative losses, (2) detect low abundanceproteins, and (3) yield precise separations for accurate differential analyses. Weare developing a liquid-based two-dimensional electrophoresis system thatpromises to maintain the high resolution possible with conventional 2-D elec-trophoresis, while at the same time providing (1) real-time monitoring of bothdimensions to control for artifactual losses; (2) reproducible separations, byvirtue of covalently bound surface buffers; and (3) high sensitivity, by reversingthe selectivity of the two-dimensional separation strategy and the use of fluores-cence labels. The elimination of convection and electroendosmosis in the systempermits high electric fields (> 500 V/cm) and rapid separation times (~30 min-utes) as additional benefits. Separations will be presented that demonstrate thepower of the system as well as show its utility in the pursuit of the goals of pro-teomics.

9:35 Application of 2-D DIGE to the Identification ofSurrogate Markers for Drug Candidates

Dr. Maribel Beaumont, Senior Scientist, DNAX Research, Inc.The cyclin dependent kinases (CDKs) play a key role in cell cycle regulation.Given this central role in proliferation and the identification of tumor-relatedabnormalities to the cell cycle machinery, the CDKs have become attractivechemotherapeutic targets for most proliferative diseases. As a number of CDKinhibitors progress into clinical trials, we chose to apply the 2-D difference in-gel electrophoresis (2-D DIGE) technology platform to identify surrogate mark-

TRACK 2PROTEIN MICROARRAYS AND

BIOMARKERS9:00 Chairperson's CommentsDr. Emanuel F. Petricoin, Co-Director, FDA-NCI Clinical ProteomicsProgram, Division of Therapeutic Products, OTRR/CBER, U.S. Food andDrug Administration

9:05 Applications for Protein and Antibody Arrays inPharmacoproteomics

Dr. Ian Humphery-Smith, Founder and Chief Scientific Officer, GlaucusProteomicsArray-based proteomics is starting to deliver on its promise of high-throughputuser-friendly and reproducible assays. Examples of such assays and their utility tothe pharmaceutical industry include screening of both therapeutic and diagnos-tic antibodies for specificity, lack of cross-reactivity (most critical), and a qualita-tive measure of affinity in a highly parallel manner—a process that can currentlytake many months per ligand. To achieve this deliverable, significant infrastruc-ture has been put in place for automated protein production and purification,extreme high-throughput PCR and ELISA, surface chemistry designed specifi-cally for protein and antibody arrays, high performance computing solutions, andprocess-wide LIMS and QA. The task of rendering high-affinity antibody pro-duction genomically relevant with respect to time and cost will also be addressed,along with other applications of both protein and antibody arrays.

9:35 Protein Biochips as New Tools in ProteomicsDr. Peter Wagner, Chief Technical Officer, Zyomyx, Inc.Novel high-throughput biomolecular analysis in genomics, proteomics, drug dis-covery, and disease diagnosis and the development and application of patient-spe-cific medicines require highly parallel, ultrasensitive, miniaturized device technolo-gies. While technological innovation in the form of DNA microarrays (gene chips)and other formats has adapted the analysis of genetic material to a miniaturized for-mat, the more delicate nature and diversity of proteins in function, structure, sta-bility, and abundance have precluded the development of analogous tools for pro-teomic analysis. In addition, a comprehensive proteomic analysis would require

1:00 Luncheon

PROTEOMICS APPLICATIONS: DRUG DISCOVERY AND

DEVELOPMENT

2:15 Chairperson's CommentsDr. Steve Holmes, Director of Therapeutic Monoclonal Antibody Development,Oxford GlycoSciences

2:20 Protein Profiling in Drug DiscoveryDr. Pat Griffin, Senior Director, Molecular Profiling Proteomics and BasicChemistry Analytical Support, Merck Research LaboratoriesDevelopment of robust, automated mass spectrometry technology coupled withthe publication of complete genome sequences along with the development oftools to compare MS data to sequence data have fueled the rapid evolution ofproteomic profiling. The impact that proteomic profiling has had on and willcontinue to have on drug discovery will take years to define. Our current effortshave centered on the development of a modular, scalable protein profiling plat-form that focuses on the deliverables (screening assays) to biology and medicinalchemistry. This platform involves interaction with biologists, statisticians and pro-filing scientists to design statistically sound experiments. These experiments gen-erate samples that are profiled using several technologies and informatics are uti-

ers that could help track dosing and efficacy of CDK inhibitors in the clinic. The2-D DIGE uses matched, spectrally resolvable fluorescent dyes to label proteinsamples prior to 2-D electrophoresis. This ability to label proteins prior to sepa-ration allows multiple samples to be co-separated on the same gel, significantlyincreasing throughput and accuracy of results, while the use of fluorescenceenables quantification over a very wide dynamic range.

10:05 Two-Dimensional Capillary Electrophoresis forSingle Cell Proteomics

Dr. Shen Hu, Department of Chemistry, University of WashingtonAn automated two-dimensional capillary electrophoresis (2D-CE) system hasbeen developed for protein analysis. A fluorogenic reagent, 3-(2-furoyl) quino-line-2-carboxaldehyde (FQ), is used to label proteins. The FQ-labeled proteinsare separated by capillary SDS-DALT electrophoresis in the first dimension cap-illary and then successively transferred from the first dimension capillary to thesecond dimension capillary for further separation by capillary zone elec-trophoresis. Laser-induced fluorescence is employed as an ultrasensitive detectorof the separated proteins. This 2-D CE system provides great resolution and sen-sitivity for proteins. It has been routinely used for single cell proteomic study inthis lab.


11:30 Phosphoproteome Analysis withPhosphopeptide Isotope-Coded Affinity Tagsand Mass Spectrometry

Dr. Thomas P. Conrads, Associate Director, Analytical Chemistry Laboratory,Mass Spectrometry Center, SAIC-Frederick, National Cancer InstituteRecent advances in analytical methods, particularly in the area of mass spec-trometry, have brought the field of proteomics to the forefront in biological sci-ence. The ultimate goal of proteomics—to characterize proteins expressed with-in a cell under a specific set of conditions—is daunting due to the complexity anddynamic nature of the protein population within the cell. While a great deal ofeffort has focused on developing methods to identify expressed proteins, theidentification of post-translational modifications is equally important for com-prehensive proteome characterization. Of all the known post-translational mod-ifications, phosphorylation arguably plays the largest role in the context of cellu-lar homeostasis. This talk will cover the recent progress we have made in devel-oping techniques not only to identify but also to quantitatively determine sitesof phosphorylation.

12:00 Towards Comprehensive Proteomic Analysis ofCells and Tissues

Dr. John R. YatesA component to understanding biological processes involves identifying the pro-teins expressed in cells as well as their modifications. A recent approach to iden-tifying protein mixtures is direct analysis of the proteolytically digested proteinsusing liquid separation techniques and tandem mass spectrometry/databasesearching. As peptide mixtures become more complex better separation tech-niques are required to resolve the peptide components for tandem mass spec-trometry. We have an approach to separate complex peptide mixtures usingmicrocolumn LC/LC in conjunction with tandem mass spectrometry. Resultson studies of yeast protein complexes, human tissues, and rat organelles will bediscussed.


measurement and characterization of protein abundance and chemical modificationsas well as discovery of unknown proteins, new pathways, and functional linkages.


11:00 Use of Protein Profiling for Discovery of ClinicalTrial Biomarkers and Drug Targets

Dr. Stephen F. Kingsmore, Chief Operating Officer, Molecular Staging, Inc.Molecular Staging is using chip-based, high-throughput protein profiling for drugdiscovery proteomics. We have developed a protein chip that measures 120 humangrowth factors, cytokines, chemokines, soluble receptors, and inducers/suppres-sors of apoptosis with ~10pg/ml sensitivity. When allied with multivariate bioin-formatic analysis tools, protein profiling of large numbers of serum, plasma, or tis-sue culture supernatants offers a powerful, new approach to drug target discovery,identification of biomarkers for prediction or assessment of drug response, andmolecular staging, classification, and subtyping of disease. Examples of the powerof drug discovery proteomics in human diseases, such as cerebral palsy and severecombined immunodeficiency, and in lead compound selection will be presented.

11:30 Epitomics: Analyzing the Global Response ofthe Immune System for Cancer DiagnosticsUsing Protein Microarrays

Dr. Michael A. Tainsky, Professor and Director, Program in Molecular Biologyand Genetics, Barbara Ann Karmanos Cancer Institute, Wayne StateUniversityWe have developed a novel screening technology for early detection of cancer usingT7 phage display cDNA libraries and differential biopanning to isolate epitopesreacting with antibodies present specifically in the sera of patients with ovarian can-cer. The goal is to use serum reactivity to proteins expressed in their ovarian tumorsas diagnostic or prognostic biomarkers. Serum reactivity toward a cellular proteinmay occur because of the presentation of a mutated form of the protein from thetumor cells or overexpression of the protein in the tumor cells. The antibody reac-tion to large numbers of these epitopes is detected in a highly parallel assay on pro-tein microarrays. We call this approach "Epitomics." Assaying serum antibodies frompatients and controls with two-color fluorescence detection on epitope biochips, wecan identify the presence of cancer in sera from women with ovarian cancer.

12:00 Use of Artificial Intelligence-BasedBioinformatics to Mine for Serum ProteomicPatterns: Applications to Early Cancer andToxicity Detection

Dr. Emanuel F. PetricoinThe search for biomarkers has mainly relied in the past on traditional proteomicapproaches, such as 2D-PAGE, in an attempt to discover new proteins that can beused for disease detection and monitoring the patient. These attempts have provenmostly futile, especially for biomarkers that are serum-based. We have invented anew approach that combines the power of artificial intelligence-based algorithmsand high-throughput proteomic fingerprinting tools such as SELDI-TOF to findspecific proteomic signatures that can distinguish healthy from diseased patients.For the first time, we have demonstrated utility of this approach by the detectionof early ovarian and prostate cancer in large blinded patient sera study sets and thedetection of early drug-induced toxicity in animal studies. The ability of the pat-tern itself to become the classifier represents a new paradigm for the applicationof proteomics to clinical specimen analysis and disease diagnosis.


lized to compare data across platforms. Our protein profiling platform consists ofseveral modules - sample preparation, fractionation, electrophoresis and proteinidentification. Our protein identification module involves the use of many typesof mass spectrometry technology such as MALDI-TOF, ESI-FT-ICR, ESI-IonTrap, AP-MALDI-Ion Trap and ESI-Q-TOF. Automation of the workflowprocesses through the use of robotics and informatic tools has improved per-formance and throughput. Samples processed by the platform have includedserum and tissue extracts.

2:50 Integrating Functional Genomics andProteomics with Drug Discovery andDevelopment

Dr. Jan van Oostrum, Executive Director, Functional Genomics, and Head ofProteome Sciences, Novartis Pharma AGSummary unavailable at time of printing

3:20 Chemistry-Directed Discovery Technology UsingProteomeScan™

Dr. David Lockhart, Chief Scientific Officer, Ambit BiosciencesOne of the major problems encountered in drug discovery today is the inabilityto rapidly screen chemicals against targets on a genomewide scale. AmbitBiosciences has developed a phage display-based technology that enables thedirect screening, in a parallel, efficient, and highly scalable manner, of tens ofthousands of human proteins for their ability to bind biologically active small mol-ecules, peptides, or proteins.


4:15 From Genomics to Proteomics to TherapeuticsDr. Kevin P. Baker, Associate Director, Department of Preclinical Discovery,Human Genome Sciences, Inc.Human Genome Sciences has developed a high-throughput therapeutic discovery

platform based on its cDNA/protein expression technologies. The focus of thisprogram is primarily on secreted proteins and receptors. The platform allows fora high-throughput functional proteomic analysis. The platform will be describedtogether with some of the advantages over conventional methods. In addition,some of the hits obtained from this program will be highlighted.

4:45 From High-Throughput Proteomics toTherapeutic Antibodies: Accelerating theDiscovery Process

Dr. Steve HolmesExpression profiling using proteomics is proving invaluable in defining the under-lying biological processes inherent in many disease states. Recent advances in bio-logical mass spectroscopy and protein analysis, combined with improved samplehandling technologies, have allowed the simultaneous characterization of thou-sands of proteins in practical time frames. Data will be presented on PrePro sam-ple preparation (cell sorting, purified membrane isolation), high-throughput pro-teomics (ICAT), and integrated bioinformatics. A major focus of this establishedpipeline is the discovery of abundant cell surface proteins differentially expressedin clinical tumor material, with the intention of generating humanized antibodytherapeutics. For a range of clinically important diseases, antibodies were gener-ated against surface proteins whose expression is unequivocally altered duringoncogenesis. The characterization of these antibodies by high-throughput flowcytometry, immunohistochemistry, and biological assays will also be reported.This presentation serves to demonstrate that considerable advantages derive fromintegrating an industrialized proteomics platform with technologies for the rapidgeneration of therapeutic antibodies.


5:45 Close of Conference

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SPONSORSHIP INFORMATIONCHI's annual Beyond Genome week is comprised of three different meetings all providing information on the latest techniques and computational tools used in theanalysis, correlation, and integration of genomic data. The individual meetings will be focused on In Silico Biology, Bioinformatics and Genome Research, andProteomics. As a way of standing out in the crowd, you might want to consider some the remaining sponsorship opportunities. Some of the more popular packagesthat are still available include exhibit space, lanyards, pocket guides, delegate bags, refreshment breaks, luncheons, and receptions.

Contact Jim MacNeil at T-617-630-1341 or by email at [email protected] to receive more information on the available booths and sponsorship packages.

EXHIBIT HALL PASS INFORMATIONBeyond Genome includes three different conferences, each with their own set of exhibitors, and will focus on the analysis, correlation, and integration of genomicdata. The exhibit hall is the center for identifying and networking with the leaders in the fields of in silico biology, bioinformatics, and proteomics. We anticipate theparticipation of over 1100 delegates and at least 50 companies to be represented over the course of the week. For a nominal fee, these passes will provide you withaccess to the exhibit hall from June 3 - 6, 2002.

To register, please see the enclosed sheet. If you cannot locate the registration form, it is also available on the web at http://www.beyondgenome.com/ex_hall-pass.htm. Please note that these passes do not include access to the conference session, tutorials, or workshops. Substitutions are not permitted and the fee is non-refundable. These passes may not be used for any unrelated business promotions or solicitation.

The following companies are already scheduled to exhibit as of February 20, 2002:

Aber Genomic Computing Ltd.

Accelyrs, Inc.

Applied Precision

Arcturus Engineering, Inc.

BD Biosciences

Capital Genomix, Inc.

Cellomics, Inc.

Compugen Ltd.

DoubleTwist, Inc.

Gene Logic, Inc.

GeneData

Genomica Corporation

Golden Helix, Inc.

Gyros AB

Incyte Genomics, Inc.

InforMax, Inc.

Inpharmatica Ltd.

Integrated Genomics, Inc.

Iobion Informatics LLC

John Wiley & Sons Ltd.

LION Bioscience AG

Mergen Ltd.

Microcal, LLC

Micromass, Inc.

Nonlinear Dynamics Ltd.

OmniViz, Inc.

Oxford Glycosciences

Paradigm Genetics, Inc.

Paragon Bioservices, Inc.

Protedyne

Rosetta Biosoftware

Silicon Genetics

Spotfire, Inc.

Third Wave Technologies

Vivascience AG

GENOMIC REPORTS

Cambridge Healthtech Institute's (CHI's) Genomic Reports are used by leading pharmaceutical,biotech, genomic, consulting, and financial companies to keep abreast of the genomics informationexplosion. These reports feature:

• Current and emerging technologies • Strategic business models • Drug and diagnostic applications

• Business activity/deals • Key scientific and business issues • Expert commentaries and insights

• "Maps" of key players and their technologies, with contact information

Genomic Reports are based on in-depth interviews with experts in the field and supported by hundreds of hours of pri-mary and secondary research. They pro-vide comprehensive coverage of strategic issues in genomics-based drug discov-eryand development in a concise and well-organized format.

The following reports are now available in electronic and print format:Proteomics: Analysis of Selected Emerging TechnologiesStructural Proteomics: High-Throughput Approaches Fuel Drug Discovery and DevelopmentBioinformatics: Getting Results in the Era of High-Throughput GenomicsMicroarrays and Related Technologies: Miniaturization and Acceleration of Genomic ResearchPharmacogenomics: Finding the Competitive Edge in Genetic Variation Target Identification and Validation: Key Approaches for Improving the Efficiency and Profitability of Drug Discovery and Development Transforming the Pharmaceutical Industry: Adapting to Change in Technology and Markets Breaking the Bottlenecks: Applying Genomics Throughout Drug Discovery and Development Commercial Implications of Advances in the Identification, Mapping, and Application of Single Nucleotide Polymorphisms High-Throughput Genomics: Maximizing Efficiency and Productivity for Drug Discovery and Development Commercialization of Genomics: Challenges and Opportunities DNA Microarray Informatics: Key Technological Trends and Commercial Opportunities Profiting from Proteomics: Entering the Age of High-ThroughputPredictive Pharmacogenomics: Revolutionizing Health Care (Spring 2002)Biochemical Pathway Analysis for Target Identificationand Validation (Spring 2002)Toxicogenomics (Spring 2002)For Genomic reports details, to order a report or to find out more information on report subscriptions, point your browser to www.chireports.com, or contactVernette Roach at 617-630-1338 or [email protected].

EXHIBIT HALL HOURS

Monday, June 3, 8:15am - 4:05pm • Tuesday, June 4, 7:30am - 5:00pm • Wednesday, June 5, 8:00am - 3:45pm

Thursday, June 6, 7:30am - 4:30pm • Friday, June 7, 8:00am - 4:45pm

Special Zone and Discount Fares have been established for this conference with United Airlines. Please call United Airlines MeetingReservation Desk at 800-521-4041 and reference ID#579YS.

Hilton San Diego Resort1775 East Mission Bay DriveSan Diego, CA 92109T: 619-276-4010F: 619-275-8944Room Rate: $195 S/DCut-off Date: May 12, 2002

Please call the hotel directly to make your roomreservation. Identify yourself as a CambridgeHealthtech Institute conference attendee to receivethe reduced room rate. Reservations made after thecut-off date or after the group room block hasbeen filled (whichever comes first) will be acceptedon a space-and-rate-availability basis. Rooms arelimited, so please book early.

Cambridge Healthtech Institute encourages atten-dees to gain further exposure by presenting theirwork in the poster sessions. Please fill out the regis-tration form, with the poster title and primaryauthor. To ensure inclusion in the conferencebinder, a one-page summary must be submitted andregistration must be paid in full by May 3, 2002.

Hotel Information

Travel Information

Call for Sponsors and Exhibitors

Call for Posters

Gene Academic, Government, Commercial Hospital-Affiliated

❒ In Silico Biology OR ❒ Bioinformatics OR ❒ Proteomics Advance Registration (by April 19, 2002) ❒ $1,035 ❒ $515On-site or Late Registration ❒ $1,190 ❒ $570❒ In Silico Biology/Bioinformatics OR ❒ Bioinformatics/Proteomics OR❒ In Silico Biology/Proteomics Advance Registration (by April 19, 2002) ❒ $1,600 ❒ $765On-site or Late Registration ❒ $1,705 ❒ $820❒ In Silico Biology/Bioinformatics/Proteomics Advance Registration (by April 19, 2002) ❒ $2,025 ❒ $985On-site or Late Registration ❒ $2,135 ❒ $1,040ISCB Member Discount ❒ $100 off fees listed above ❒ $50 off fees listed above

All attendees of CHI’s genomic events will receive a complimentary subscription to CHI’s Genome Link e-newsletter. If you do not wish toreceive a subscription, please check this box. ❒❒ I cannot attend but would like to purchase a copy of the documentation ❒❒ binder or ❒❒ CD for $235 each (plus shipping).❒ In Silico Biology OR ❒ Bioinformatics OR ❒ Proteomics.❒ Please send information on exhibiting and opportunities to present workshops.❒ I am interested in presenting a poster at ❒ In Silico Biology OR ❒ Bioinformatics OR ❒ Proteomics

and will submit a completed one-page abstract by May 3, 2002. (Please Note: Registration must be paid in full to present poster.)Title

❒ Mr. ❒ Ms. ❒ Mrs. ❒ Dr. ❒ Prof.

First Name Last Name




Title Div./Dept.

Company

Address

City/State/Postal Code Country

Telephone Fax

E-Mail

❒ Enclosed is a check or money order payable to Cambridge Healthtech Institute, drawn on a U.S. bank, in U.S. currency.❒ Invoice me, but reserve my space with credit card information listed below. Invoices unpaid one week prior to conference will be

charged to credit card at full registration rate. Invoices must be paid in full and checks received by the deadline date to retain regis-tration discount. If you plan to register on site, please check with CHI beforehand for space availability.

❒ Please charge: ❒ AMEX (15 digits) ❒ Visa (13-16 digits) ❒ MasterCard (16 digits) ❒ Diners Club (14 digits)

Card # Exp. Date

Cardholder

Signature

Cardholder’s Address (if different from above)

City/State/Postal Code Country

FAX or MAIL your registration to: Cambridge Healthtech Institute, 1037 Chestnut Street, Newton Upper Falls, MA 02464T: 617-630-1300 or toll-free in the U.S. 888-999-6288 • F: 617-630-1325 • www.beyondgenome.com

HOW DID YOU FIRST HEARABOUT THIS MEETING?

❒ Brochure

❒ Colleague

❒ Ad (publication name or web address)

❒ CHI Web Site

❒ Other

Please send information on related CHI programs:

❒ Pep Talk

❒ Integrated Bioinformatics (BNE)

❒ Proteins to Profits (PRE/PCE)

❒ Genome Tri-Conference

Register 3—4th Is FreeIndividuals must register for the same conferenceor conference combination and submit complet-ed registration forms together for discount toapply. Call for details on groups of 5 or more.(Applicable to paid registrations only.)

Additional Registration DetailsEach registration includes all conference sessions,posters and exhibits, one luncheon, one recep-tion, continental breakfasts, all refreshmentbreaks, and a copy of the document binder.

Handicapped Equal AccessIn accordance with the ADA, CambridgeHealthtech Institute is pleased to arrange specialaccommodations for attendees with specialneeds. All requests for such assistance must besubmitted in writing to CHI at least 30 daysprior to the start of the meeting.

Substitution/Cancellation PolicyIn the event that you need to cancel a registra-tion, you may:• Transfer your registration to a colleague within

your organization• Credit your registration to another Cambridge

Healthtech Institute program• Request a refund minus a $75 processing fee

per conference• Request a refund minus the cost of ordering a

copy of the document binder(s) or CD(s) at$235 per copy

NOTE: Cancellations will only be accepted up toone week prior to the conference.

Program and speakers are subject to change.

YES! Register me for ■■ In Silico Biology ■■ Bioinformatics ■■ Proteomics 815/816/817 PDF

IHD

You canregister online at

www.beyondgenome.com

Our annual Beyond Genome week comprises three different meetings all providing information on the latest techniques and compu-tational tools used in the analysis, correlation, and integration of genomic data. The individual meetings will focus on In Silico Biology,Bioinformatics and Genome Research, and Proteomics. With over 30 companies already registered to exhibit, this event will be soldout soon! As a way of standing out in the crowd, you might want to consider some of the remaining sponsoship opportunities. Themore popular packages include exhibit space, refreshment breaks, luncheons, receptions, hospitality suites, and the entire event. Theadvance deadline of April 12, 2002 is fast approaching—registering to exhibit before that date will save your company up to $700!Contact Jim MacNeil at 617-630-1341 or by email at [email protected] to receive more information on the available sponsor-ship packages.

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cambridge healthtech institute’s...beyond genome is a six-day event covering computational tools...

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