1. 10/29/2004 Bioinformatics in Computer Science 1 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

2. 10/29/2004 Bioinformatics in Computer Science 2 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

3. 10/29/2004 Bioinformatics in Computer Science 3 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

4. 10/29/2004 Bioinformatics in Computer Science 4 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)

5. 10/29/2004 Bioinformatics in Computer Science 5 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

6. 10/29/2004 Bioinformatics in Computer Science 6 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

7. 10/29/2004 Bioinformatics in Computer Science 7 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

8. 10/29/2004 Bioinformatics in Computer Science 8 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

9. 10/29/2004 Bioinformatics in Computer Science 9 The Players Computer Science Virginia Bioinformatics Institute (VBI) Others at VT

10. 10/29/2004 Bioinformatics in Computer Science 10 CS Bioinformatics Faculty 1.Chris Barrett (VBI, CS) 2.Vicky Choi 3.Roger Ehrich 4.Edward A. Fox 5.Lenny Heath 6.T. M. Murali 7.Chris North 8.Alexey Onufriev 9.Naren Ramakrishnan 10.Adrian Sandu 11.Eunice Santos 12.João Setubal (VBI, CS) 13.Cliff Shaffer 14.Layne Watson 15.Liqing Zhang

11. 10/29/2004 Bioinformatics in Computer Science 11 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

12. 10/29/2004 Bioinformatics in Computer Science 12 Established Bioinformatics Faculty Layne Watson Lenny Heath Cliff Shaffer Naren Ramakrishnan Eunice Santos

13. 10/29/2004 Bioinformatics in Computer Science 13 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

14. 10/29/2004 Bioinformatics in Computer Science 14 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

15. 10/29/2004 Bioinformatics in Computer Science 15 Cliff Shaffer Associate Professor of Computer Science Expertise: algorithms; problem solving environments; spatial data structures; JigCell: cell-cycle modeling environment; with Ramakrishnan, Tyson, Watson

16. 10/29/2004 Bioinformatics in Computer Science 16 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

17. 10/29/2004 Bioinformatics in Computer Science 17 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

18. 10/29/2004 Bioinformatics in Computer Science 18 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

19. 10/29/2004 Bioinformatics in Computer Science 19 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

20. 10/29/2004 Bioinformatics in Computer Science 20 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

21. 10/29/2004 Bioinformatics in Computer Science 21 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

22. 10/29/2004 Bioinformatics in Computer Science 22 João Setubal Research Associate Professor at VBI Associate Professor of Computer Science Joined in early 2004 Expertise: algorithms; computational biology; bacterial genomes Comparative genomics

23. 10/29/2004 Bioinformatics in Computer Science 23 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

24. 10/29/2004 Bioinformatics in Computer Science 24 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

25. 10/29/2004 Bioinformatics in Computer Science 25 Bioinformatics Research in CS Collaboration Funding Resources Overview of projects

26. 10/29/2004 Bioinformatics in Computer Science 26 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

27. 10/29/2004 Bioinformatics in Computer Science 27 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.

28. 10/29/2004 Bioinformatics in Computer Science 28 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. NSF EIA-01903660: A Microarray Experiment Management System. N. Ramakrishnan, L. S. Heath, L. T. Watson, R. Grene, J. W. Weller (VBI). $600,000. DARPA N00014-01-1-0852: 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.

29. 10/29/2004 Bioinformatics in Computer Science 29 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

30. 10/29/2004 Bioinformatics in Computer Science 30 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

31. 10/29/2004 Bioinformatics in Computer Science 31 Clb5 MBF P Sic1 SCF Sic1 Swi5 Clb2 Mcm1 Unaligned chromosomes Cln2 Clb2 Clb5 Cdc20 Cdh1 Cdc20 APC PPX Mcm1 SBF Esp1 Pds1 Cdc20 Net1 Net1P Cdc14 RENT Cdc14 Cdc15 Tem1 Bub2 CDKs Esp1 Mcm1 Mad2 Esp1 Unaligned chromosomes Cdc15 Lte1 Budding Cln2 SBF ? Cln3 Bck2 and growth Sister chromatid separation DNA synthesis Cell Cycle of Budding Yeast

32. 10/29/2004 Bioinformatics in Computer Science 32 JigCell Problem-Solving Environment Experimental Database Wiring Diagram Differential EquationsParameter Values Analysis Simulation Visualization Automatic Parameter Estimation

33. 10/29/2004 Bioinformatics in Computer Science 33 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.

34. 10/29/2004 Bioinformatics in Computer Science 34 Expresso: A Next Generation Software System for Microarray Experiment Management and Data Analysis

35. 10/29/2004 Bioinformatics in Computer Science 35 Scenarios for Effects of Abiotic Stress on Gene Expression in Plants

36. 10/29/2004 Bioinformatics in Computer Science 36 The Expresso Pipeline

37. 10/29/2004 Bioinformatics in Computer Science 37 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

38. 10/29/2004 Bioinformatics in Computer Science 38 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?

39. 10/29/2004 Bioinformatics in Computer Science 39 Reconciling Networks Munnik and Meijer, FEBS Letters, 2001 Shinozaki and Yamaguchi- Shinozaki, Current Opinion in Plant Biology, 2000

40. 10/29/2004 Bioinformatics in Computer Science 40 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

41. 10/29/2004 Bioinformatics in Computer Science 41 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

42. 10/29/2004 Bioinformatics in Computer Science 42 Fusion — Chris North “Snap together” visualization environment Interactively linked data from multiple sources Data mining in the background

43. 10/29/2004 Bioinformatics in Computer Science 43 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 Virginia Bioinformatics Institute (VBI) –Mathematics –Physics –Simulation –Statistics

44. 10/29/2004 Bioinformatics in Computer Science 44 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. VBI Mission Statement

45. 10/29/2004 Bioinformatics in Computer Science 45 The Disease Triangle

46. 10/29/2004 Bioinformatics in Computer Science 46 Core lab facilities –DNA sequencing –Gene expression –Proteomics –Metabolomics Core computational facilities –Cluster computing dedicated to bioinformatics –Data storage –Visualization –Database administration Specialized VBI Facilities

47. 10/29/2004 Bioinformatics in Computer Science 47 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 VBI Integration into Main Campus

48. 10/29/2004 Bioinformatics in Computer Science 48 VBI Research Portfolio ( by sponsor ) 38% 25% 12% 5% 1% National Institutes of Health National Science Foundation VT (JHU/ASPIRES/VTF) U.S. Dept of Defense CTRF Other Academic Institutions Industry U.S. Dept of Agriculture Foundations

49. 10/29/2004 Bioinformatics in Computer Science 49 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

50. 10/29/2004 Bioinformatics in Computer Science 50 Opportunities for CS and the College of Engineering Collaboration with VBI SBES, Wake Forest School of Medicine NIH and DHS funding Scientific modeling

51. 10/29/2004 Bioinformatics in Computer Science 51 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

52. 10/29/2004 Bioinformatics in Computer Science 52 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

53. 10/29/2004 Bioinformatics in Computer Science 53 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

54. 10/29/2004 Bioinformatics in Computer Science 54 Scientific Modeling Protein folding Protein function Protein-protein interaction Cellular signaling and decision processes Heart, lung, neurological function System X is an essential component

55. 10/29/2004 Bioinformatics in Computer Science 55 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