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Bioinformatics in Computer Science, the Virginia Bioinformatics Institute, and Opportunities for Engineering. Lenwood S. Heath Department of Computer Science Blacksburg, VA 24061. College of Engineering Advisory Board Meeting October 29, 2004. Overview.

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slide1

Bioinformatics in Computer Science, the Virginia Bioinformatics Institute, and Opportunities for Engineering

Lenwood S. Heath

Department of Computer Science

Blacksburg, VA 24061

College of Engineering

Advisory Board Meeting

October 29, 2004

10/29/2004 Bioinformatics in Computer Science

overview
Overview
  • Computational biology and bioinformatics
  • The players
    • Computer Science
    • Virginia Bioinformatics Institute (VBI)
    • Others at VT
  • Opportunities for the College
    • Collaboration with VBI
    • SBES, Wake Forest School of Medicine
    • NIH and DHS funding
    • Scientific modeling

10/29/2004 Bioinformatics in Computer Science

computational biology and bioinformatics
Computational Biology and Bioinformatics
  • Computational biology — computational research inspired by biology
  • Bioinformatics — application of computational research (computer science, mathematics, statistics) to advance basic and applied research in the life sciences
    • Agriculture
    • Basic biological science
    • Medicine
  • Both ideally done within multidisciplinary collaborations

10/29/2004 Bioinformatics in Computer Science

bioinformatics at vt part i
Bioinformatics at VT (Part I)
  • Biological modeling (Tyson, Watson): > 20 years
  • Computational biology, genome rearrangements (Heath): > 10 years
  • Fralin Biotechnology sponsored faculty advisory committee centered on bioinformatics: 1998-2000
    • Biochemistry; biology; CALS; computer science (Heath, Watson); statistics; VetMed
    • Provost provided $1 million seed money
    • First VT bioinformatics hire (Gibas, biology, 1999)

10/29/2004 Bioinformatics in Computer Science

bioinformatics at vt part ii
Bioinformatics at VT (Part II)
  • Outside initiative submitted to VT for a campus bioinformatics center — 1998
  • Discussions of bioinformatics advisory committee contributed to a proposal to the Gilmore administration — 1999
  • Governor Gilmore puts plans and money for bioinformatics center in budget — 1999-2000
  • Virginia Bioinformatics Institute (VBI) established July, 2000; housed in CRC

10/29/2004 Bioinformatics in Computer Science

bioinformatics at vt part iii
Bioinformatics at VT (Part III)
  • Bioinformatics course and curriculum development began with faculty subcommittee — 1999
  • Courses supporting bioinformatics now in many life science and computational science departments, including:
    • Biology
    • Biochemistry
    • Computer Science
    • Plant Pathology, Physiology, and Weed Science (PPWS)
    • Mathematics
    • Statistics

10/29/2004 Bioinformatics in Computer Science

bioinformatics education at vt
Bioinformatics Education at VT
  • CS has been training CS graduate students in bioinformatics since 2000
  • Graduate bioinformatics option established in a number of participating departments — 2003
  • Ph.D. program in Genetics, Bioinformatics, and Computational Biology (GBCB) — 2003
  • First GBCB students arrived, Fall, 2003; now in second year; completing core requirements

10/29/2004 Bioinformatics in Computer Science

bioinformatics spirit at vt
Bioinformatics Spirit at VT
  • Close collaboration between life scientists and computational scientists from the beginning
  • Educational approach insists on adequate multidisciplinary background
  • Multidisciplinary collaborators work closely on a regular basis
  • Contributions to biology or medicine essential outcomes

10/29/2004 Bioinformatics in Computer Science

the players
The Players
  • Computer Science
  • Virginia Bioinformatics Institute (VBI)
  • Others at VT

10/29/2004 Bioinformatics in Computer Science

cs bioinformatics faculty
CS Bioinformatics Faculty
  • Chris Barrett (VBI, CS)
  • Vicky Choi
  • Roger Ehrich
  • Edward A. Fox
  • Lenny Heath
  • T. M. Murali
  • Chris North
  • Alexey Onufriev
  • Naren Ramakrishnan
  • Adrian Sandu
  • Eunice Santos
  • João Setubal (VBI, CS)
  • Cliff Shaffer
  • Layne Watson
  • Liqing Zhang

10/29/2004 Bioinformatics in Computer Science

relevant expertise
Relevant Expertise
  • Algorithms— Choi, Heath, Santos, Setubal, Shaffer, Watson
  • Computational structural biology — Onufriev, Sandu
  • Computational systems biology — Murali
  • Data mining — Ramakrishnan
  • Genomics — Heath, Murali, Ramakrishnan, Setubal, Zhang
  • Human-computer interaction, visualization — North
  • Image processing — Ehrich, Watson
  • Information retrieval — Ehrich
  • High performance computing— Sandu, Santos, Watson
  • Optimization — Watson
  • Simulation — Barrett

10/29/2004 Bioinformatics in Computer Science

established bioinformatics faculty
Established Bioinformatics Faculty
  • Layne Watson
  • Lenny Heath
  • Cliff Shaffer
  • Naren Ramakrishnan
  • Eunice Santos

10/29/2004 Bioinformatics in Computer Science

layne watson
Layne Watson
  • Professor of Computer Science and Mathematics
  • Expertise: algorithms; image processing; high performance computing; optimization; scientific computing
  • Computational biology: has worked with John Tyson (biology) for over 20 years
  • JigCell: cell-cycle modeling environment; with Tyson, Shaffer, Ramakrishnan, Pedro Mendes of VBI
  • Expresso: microarray experimentation; with Heath, Ramakrishnan

10/29/2004 Bioinformatics in Computer Science

lenny heath
Lenny Heath
  • Professor of Computer Science
  • Expertise: algorithms; theoretical computer science; graph theory
  • Computational biology: worked in genome rearrangements 10 years ago
  • Bioinformatics: concentration in past 5 years
  • Expresso: microarray experimentation; with Ramakrishnan, Watson
    • Multimodal networks
    • Computational models of gene silencing

10/29/2004 Bioinformatics in Computer Science

cliff shaffer
Cliff Shaffer
  • Associate Professor of Computer Science
  • Expertise: algorithms; problem solving environments; spatial data structures;
  • JigCell: cell-cycle modeling environment; with Ramakrishnan, Tyson, Watson

10/29/2004 Bioinformatics in Computer Science

naren ramakrishnan
Naren Ramakrishnan
  • Associate Professor of Computer Science
  • Expertise: data mining; machine learning; problem solving environments
  • JigCell: cell-cycle modeling problem solving environment; with Shaffer, Watson
  • Expresso: microarray experimentation; with Heath, Watson
    • Proteus — inductive logic programming system for biological applications
    • Computational models of gene silencing

10/29/2004 Bioinformatics in Computer Science

eunice santos
Eunice Santos
  • Associate Professor of Computer Science
  • Expertise: Algorithms;computational biology;computational complexity; parallel and distributed processing; scientific computing
  • Relevant bioinformatics project: modeling progress of breast cancer

10/29/2004 Bioinformatics in Computer Science

new bioinformatics faculty
New Bioinformatics Faculty
  • T. M. Murali (2003) CS bioinformatics hire
  • Alexey Onufriev (2003) CS bioinformatics hire
  • Adrian Sandu(2004) CS hire
  • João Setubal (Early 2004) VBI and CS
  • Vicky Choi (2004) CS bioinformatics hire
  • Liqing Zhang (2004) CS bioinformatics hire
  • Chris Barrett (Fall 2004) VBI and CS
  • One more bioinformatics position for Fall, 2005

10/29/2004 Bioinformatics in Computer Science

t m murali
T. M. Murali
  • Assistant Professor of Computer Science
  • Hired in 2003 for bioinformatics group
  • Expertise: algorithms; computational geometry; computational systems biology
  • Projects:
    • Functional gene annotation
    • xMotif — find patterns of coexpression among subsets of genes
    • RankGene — rank genes according to predictive power for disease

10/29/2004 Bioinformatics in Computer Science

alexey onufriev
Alexey Onufriev
  • Assistant Professor of Computer Science
  • Hired in 2003 for bioinformatics group
  • Expertise: Computational and theoretical biophysics and chemistry; structural bioinformatics; numerical methods; scientific programming
  • Projects:
    • Biomolecular electrostatics
    • Theory of cooperative ligand binding
    • Protein folding
    • Protein dynamics — how does myoglobin uptake oxygen?
    • Computational models of gene silencing

10/29/2004 Bioinformatics in Computer Science

adrian sandu
Adrian Sandu
  • Associate Professor of Computer Science
  • Hired in 2003
  • Expertise: Computational science; numerical methods; parallel computing; scientific and engineering applications
  • Computational science:
    • New generation of air quality models
    • computational tools for assimilation of atmospheric chemical and optical measurements into atmospheric chemical transport models

10/29/2004 Bioinformatics in Computer Science

jo o setubal
João Setubal
  • Research Associate Professor at VBI
  • Associate Professor of Computer Science
  • Joined in early 2004
  • Expertise: algorithms; computational biology; bacterial genomes
  • Comparative genomics

10/29/2004 Bioinformatics in Computer Science

vicky choi
Vicky Choi
  • Assistant Professor of Computer Science
  • Hired in 2004 for bioinformatics group
  • Expertise: computational biology; algorithms
  • Projects:
    • Algorithms for genome assembly
    • Protein docking
    • Biological pathways

10/29/2004 Bioinformatics in Computer Science

liqing zhang
Liqing Zhang
  • Assistant Professor of Computer Science
  • Hired in 2004 for bioinformatics group
  • Expertise: evolutionary biology; bioinformatics
  • Research interests:
    • Comparative evolutionary genomics
    • Functional genomics
    • Multi-scale models of bacterial evolution

10/29/2004 Bioinformatics in Computer Science

bioinformatics research in cs
Bioinformatics Research in CS
  • Collaboration
  • Funding
  • Resources
  • Overview of projects

10/29/2004 Bioinformatics in Computer Science

selected collaborations
Selected Collaborations
  • Virginia Tech: Biochemistry, Biology, Fralin Biotechnology Center, PPWS, Veterinary Medicine, VBI, Wood Science
  • North Carolina State University: Forest Biotechnology Center
  • Duke: Biology
  • University of Illinois: Plant Biology

10/29/2004 Bioinformatics in Computer Science

selected funding watson tyson
Selected Funding (Watson/Tyson)
  • NSF MCB-0083315: Biocomplexity---Incubation Activity: A Collaborative Problem Solving Environment for Computational Modeling of Eukaryotic Cell Cycle Controls. J. J. Tyson,L. T. Watson, N. Ramakrishnan, C. A. Shaffer,J. C. Sible.$99,965.
  • NIH 1 R01 GM64339-01: ``Problem Solving Environment for Modeling the Cell Cycle. J. J. Tyson, J. Sible, K. Chen,L. T. Watson, C. A. Shaffer, N. Ramakrishnan,P. Mendes (VBI). $211,038.
  • Air Force Research Laboratory F30602-01-2-0572: The Eukaryotic Cell Cycle as a Test Case for Modeling Cellular Regulation in a Collaborative Problem Solving Environment. J. J. Tyson, J. C. Sible, K. C. Chen,L. T. Watson, C. A. Shaffer, N. Ramakrishnan.$1,650,000.

10/29/2004 Bioinformatics in Computer Science

selected funding heath et al
Selected Funding (Heath, et al.)
  • NSF IBN 0219322: ITR: Understanding Stress Resistance Mechanisms in Plants: Multimodal Models Integrating Experimental Data, Databases, and the Literature. L. S.Heath;R. Grene, B. I. Chevone,N. Ramakrishnan,L. T. Watson.$499,973.
  • NSFEIA-01903660: A Microarray Experiment Management System. N. Ramakrishnan, L. S. Heath, L. T. Watson,R. Grene,J. W. Weller (VBI). $600,000.
  • DARPAN00014-01-1-0852: Dryophile Genes to Engineer Stasis-Recovery of Human Cells. M. Potts,L. S. Heath,R. F. Helm, N. Ramakrishnan, T. O. Sitz, F. Bloom, P. Price (Life Technologies), J. Battista (LSU). $4,532,622.
  • NSF CCF 0428344: ITR-(NHS)-(sim): Computational Models for Gene Silencing: Elucidating a Pervasive Biological Defensive Response. L. S.Heath,R. F. Helm,A. Onufriev, M. Potts,N. Ramakrishnan.$1,500,000.

10/29/2004 Bioinformatics in Computer Science

research resources available to cs bioinformatics
Research Resources Available to CS Bioinformatics

System X

  • Third fastest computer on the planet (2003)

Laboratory for Advanced Scientific Computing & Applications (LASCA)

  • Parallel algorithms & math software
  • Anantham Cluster
  • Grid computing

Bioinformatics Research LAN

  • Linux, Mac OS X
  • Bioinformatics databases and analysis

10/29/2004 Bioinformatics in Computer Science

jigcell a pse for eukaryotic cell cycle controls
JigCell: A PSE for Eukaryotic Cell Cycle Controls

Marc Vass, Nick Allen, Jason Zwolak, Dan Moisa,

Clifford A. Shaffer, Layne T. Watson,

Naren Ramakrishnan, and John J. Tyson

Departments of Computer Science and Biology

10/29/2004 Bioinformatics in Computer Science

slide31

Cell Cycle of Budding Yeast

Cln2

Clb2

Clb5

Sic1

Sic1

P

Sister chromatid separation

Cdc20

PPX

Lte1

Esp1

Budding

Pds1

Tem1

Esp1

Net1P

Esp1

Bub2

Cdc15

Cln2

SBF

Unaligned chromosomes

Pds1

SBF

Net1

RENT

Mcm1

Unaligned chromosomes

Cdh1

Mcm1

Cdc20

Mad2

Cdc20

Cdc14

Cln3

Cdc15

and

Bck2

Cdh1

Mcm1

APC

Clb2

Cdc14

growth

CDKs

Swi5

SCF

Cdc14

?

Cdc20

MBF

Clb5

Esp1

DNA synthesis

10/29/2004 Bioinformatics in Computer Science

slide32

Experimental Database

WiringDiagram

DifferentialEquations

ParameterValues

Simulation

Analysis

Visualization

Automatic Parameter Estimation

JigCell Problem-Solving Environment

10/29/2004 Bioinformatics in Computer Science

slide33

Why do these calculations?

  • Is the model “yeast-shaped”?
  • Bioinformatics role: the model organizes experimental information.
  • New science: prediction, insight

JigCell is part of the DARPA BioSPICE suite of software tools for computational cell biology.

10/29/2004 Bioinformatics in Computer Science

slide34

Expresso:

A Next Generation Software System for Microarray Experiment Management and Data Analysis

10/29/2004 Bioinformatics in Computer Science

slide35

Scenarios for Effects of Abiotic Stress on Gene Expression in Plants

10/29/2004 Bioinformatics in Computer Science

slide36

The Expresso Pipeline

10/29/2004 Bioinformatics in Computer Science

slide37

Proteus — Data Mining with ILP

  • ILP (inductive logic programming) — a data mining algorithm for inferring relationships or rules
  • Proteus — efficient system for ILP in bioinformatics context
  • Flexibly incorporates a priori biological knowledge (e.g., gene function) and experimental data (e.g., gene expression)
  • Infers rules without explicit direction

10/29/2004 Bioinformatics in Computer Science

slide38

Networks in Bioinformatics

  • Mathematical Model(s) for Biological Networks
  • Representation: What biological entities and parameters to represent and at what level of granularity?
  • Operations and Computations: What manipulations and transformations are supported?
  • Presentation: How can biologists visualize and explore networks?

10/29/2004 Bioinformatics in Computer Science

slide39

Reconciling Networks

Munnik and Meijer,

FEBS Letters, 2001

Shinozaki and Yamaguchi-Shinozaki, Current Opinion in Plant Biology, 2000

10/29/2004 Bioinformatics in Computer Science

slide40

Multimodal Networks

  • Nodes and edges have flexible semantics to represent:
    • Time
    • Uncertainty
    • Cellular decision making; process regulation
    • Cell topology and compartmentalization
    • Rate constants
    • Phylogeny
  • Hierarchical

10/29/2004 Bioinformatics in Computer Science

slide41

Using Multimodal Networks

  • Help biologists find new biological knowledge
  • Visualize and explore
  • Generating hypotheses and experiments
  • Predict regulatory phenomena
  • Predict responses to stress
  • Incorporate into Expresso as part of closing the loop

10/29/2004 Bioinformatics in Computer Science

fusion chris north
Fusion — Chris North
  • “Snap together” visualization environment
  • Interactively linked data from multiple sources
  • Data mining in the background

10/29/2004 Bioinformatics in Computer Science

slide43

Virginia Bioinformatics Institute (VBI)

  • Established by the state in July, 2000; high visibility
  • Applies computational and information technology in biological research
  • Research faculty (currently, about 18) expertise includes
    • Biochemistry
    • Comparative Genomics
    • Computer Science
    • Drug Discovery
    • Human and Plant Pathogens
  • More than $43 million funded research
  • Mathematics
  • Physics
  • Simulation
  • Statistics

10/29/2004 Bioinformatics in Computer Science

slide44

VBI Mission Statement

At The Virginia Bioinformatics Institute, we research biological systems and design, develop and disseminate technologies to make discoveries that improve the quality of human life.

We focus on understanding biology through systems that integrate the interaction between organisms and their environment for the benefit of science and society.

We also strive to collaborate with the scientific community by enabling transformation of information into useful knowledge and by providing scientific services.

10/29/2004 Bioinformatics in Computer Science

slide45

The Disease Triangle

10/29/2004 Bioinformatics in Computer Science

slide46

Specialized VBI Facilities

  • Core lab facilities
    • DNA sequencing
    • Gene expression
    • Proteomics
    • Metabolomics
  • Core computational facilities
    • Cluster computing dedicated to bioinformatics
    • Data storage
    • Visualization
    • Database administration

10/29/2004 Bioinformatics in Computer Science

slide47

VBI Integration into Main Campus

  • Originally housed in Corporate Research Center
  • Partially moved to campus last year — Bioinformatics I building
  • Final move to campus, December, 2004 — Bioinformatics II building
  • Total space in Bioinformatics I and II will be 130,560 square feet

10/29/2004 Bioinformatics in Computer Science

slide48

38%

1%

National Institutes of Health

1%

National Science Foundation

1%

VT (JHU/ASPIRES/VTF)

5%

U.S. Dept of Defense

5%

CTRF

Other Academic Institutions

Industry

12%

U.S. Dept of Agriculture

Foundations

25%

12%

VBI Research Portfolio ( by sponsor )

10/29/2004 Bioinformatics in Computer Science

slide49

Funded Partnerships with VT Departments

  • Aerospace and Ocean Engineering
  • Biochemistry
  • Biology
  • Biomedical Science and Pathobiology, VMRCVM
  • Computer Science
  • Crop and Soil Environmental Sciences
  • Electrical and Computer Engineering
  • Fisheries and Wildlife Science
  • Horticulture
  • Mathematics
  • Plant Pathology, Physiology, and Weed Science
  • Statistics

10/29/2004 Bioinformatics in Computer Science

opportunities for cs and the college of engineering
Opportunities for CS and the College of Engineering
  • Collaboration with VBI
  • SBES, Wake Forest School of Medicine
  • NIH and DHS funding
  • Scientific modeling

10/29/2004 Bioinformatics in Computer Science

collaboration with vbi
Collaboration with VBI
  • Basic biological science — molecular biology, functional genomics, systems biology
  • Computational methods to answer biological questions from vast stores of VBI data resources
  • Computational models and simulation of biological systems, e.g., host-pathogen interaction

10/29/2004 Bioinformatics in Computer Science

sbes wake forest
SBES, Wake Forest
  • Medical research includes significant computational challenges
  • Much analysis can be done without additional lab biology
  • Biomedical data analysis and mining
  • Identification of genes responsible for complex traits
  • More flexible and useful medical instrumentation
  • Precise identification of disease
  • Treatment suggestion
  • Prognosis prediction

10/29/2004 Bioinformatics in Computer Science

nih and dhs funding
NIH and DHS Funding
  • Bioinformatics is one of the New Pathways to Discovery in the NIH Roadmap
  • Computation is essential to advancing medical practice, from diagnosis to drug design
  • Department of Homeland Security (DHS) is funding research to respond to bioterrorism
    • Detection and identification of agents
    • Rapid response to threats
    • Modeling crisis impact and response

10/29/2004 Bioinformatics in Computer Science

scientific modeling
Scientific Modeling
  • Protein folding
  • Protein function
  • Protein-protein interaction
  • Cellular signaling and decision processes
  • Heart, lung, neurological function
  • System X is an essential component

10/29/2004 Bioinformatics in Computer Science

conclusion
Conclusion
  • Bioinformatics is an emerging area of opportunity, but challenging to enter
  • Rapid developments the norm; flexibility essential
  • Virginia Tech and the College are well-positioned to take advantage

10/29/2004 Bioinformatics in Computer Science