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Computational Biology and Approaches

Computational Biology and Approaches. Raquell M. Holmes, Ph.D. Computational Biology Workshop Howard University and Boston University. August 15, 2005. This morning. Computational Biology Snapshots of existing models Transition in biological views Computing and computational science.

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Computational Biology and Approaches

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  1. ComputationalBiology and Approaches Raquell M. Holmes, Ph.D. Computational Biology Workshop Howard University and Boston University August 15, 2005

  2. This morning Computational Biology • Snapshots of existing models • Transition in biological views Computing and computational science

  3. Computational Biology • Bioinformatics, Genomics, Proteomics, Metabolome • Sequences analysis and comparison • Database searches • Statistics, Graph theory, Strings, Markov Models • High throughput data generation • Protein structure, folding, energy • Molecular dynamics, Monte Carlo

  4. Computational Biology: Dynamics Jacquet et al 2003, JCB

  5. What exists…

  6. Actin polymers: models http://www.cytochemistry.net/Cell-biology/actin_filaments.htm

  7. Ways of studying properties • Microscope: • Watch growth and shrinkage • Use fluorescent probes for growth, shrinkage, orientation • Rates of monomer addition Myosin, actin, ATP In_vitro_motility_assay

  8. Gallery Heart muscle fibers http://www.psc.edu/research/graphics/gallery/heart.html Daniel Mocanu, Joachim Kettenbach, Michael O. Sweeney, Bruce H. KenKnight, Ron Kikinis and Solomon R. Eisenberg –Boston University

  9. Neuromuscular junction … All images were produced by Joel Stiles using DReAMM (www.mcell.psc.edu/DReAMM) software. Citation:  Stiles, JR, Ford, WC, Pattillo, JM, Deerinck, TE, Ellisman, MH, Bartol, TM, and Sejnowski, TJ. (2004) Spatially realistic computational physiology: past, present, and future. In: Parallel Computing: Software Technology, Algorithms, Architectures & Applications, ed. Joubert, G, et al. Elsevier, Amsterdam

  10. Posterior patterns determination

  11. Network for Wing Formation

  12. Conceptual models are changing

  13. Classical View of MAPK Pathways adapted from C.Roberts, et al., Science, 287, 873 (2000)

  14. The Protein Network View • Highly interconnected, not just a linear pathway! • Some proteins are missing from the protein interaction data sets (Cdc42, Ste20). • Includes several additional proteins (especially Akr1, Kss1). adapted from C.Roberts, et al., Science, 287, 873 (2000)

  15. Expression data • KEGG: • retrievable expression data sets • EcoCyc: • input expression data to view in relation to metabolic data. • Expression data is one way of viewing the behavior of a system.

  16. Submitted by: Hirotada MORI Organism: E.coli Raw data

  17. MicroArray Data: fold changes in expression Hypothetical data • Changes in gene expression: • Single time point,Various conditions • Multiple time points, One condition • GenMapp tools highlight changes

  18. Views from the Center for Cell Dynamics • Experimentalist use of confocal microscope • Static 3D image: microtubules and cytokinesis (Garry Odell) • Live label: GFP-EB1 in S. droebachiensis. (Mike Danilchik & George von Dassow) • Model Animation • Aster microtubules (George von Dassow)

  19. Views from the Center for Cell Dynamics Static 3D image: microtubules and cytokinesis (Garry Odell) • Experimentalist use of confocal microscope • ImageJ, maximum projection • Digital capture- single processor Movie source http://raven.zoology.washington.edu/celldynamics/gallery

  20. Views from the Center for Cell Dynamics Live label: GFP-EB1 in S. droebachiensis. (Mike Danilchik & George von Dassow) • Experimentalist use of confocal microscope • Spinning confocal, multiple frame captures, a single plane • Digital capture- single processor Simulation Movie source http://raven.zoology.washington.edu/celldynamics/gallery

  21. Views from the Center for Cell Dynamics Model Animation Aster microtubules (George von Dassow) • assigned color values, • numerical simulation results. • multiple processors Movie source http://raven.zoology.washington.edu/celldynamics/gallery

  22. What do we discover? • New questions: • Hysteresis in cell cycle • New understandings and conceptual models: • Metabolic control analysis • Missing pieces: • Calcium dynamics in neuroblastoma cells

  23. Science Discipline Physics, Chemistry, Biology, etc. Computer Science Hardware/Software Applied Mathematics Numerical Analysis, Modeling, Simulation Computational Science:Interdisciplinary Research and Education Slide by Kris Stewart, EdCenter, San Diego State University

  24. Elements of Computational Science Landau and Yasar, SIAM Review 2003 EPIC-Virtual Institute, 2005 • Computational tools • High performance computing* • Applied mathematics and computational methods* • Application in science and engineering* • Simulation and modeling • Visualization tools • Large scaledata sets: statistical and visual analysis

  25. What is Supercomputing?Leading Edge to Consumer Electronics 1985 Cray X-MP: 1.2 Gflop Cost:$8,000,000 60,000 watts of power No Built in Graphics 56 kbps NSFnet Backbone 2005 X-Box: ~5 Gflop peak Cost: $140 ~100 watts of power 3D Graphics (125M P/S) (100 Mbps etherNet)

  26. CI Vision http://www.nsf.gov/news/special_reports/cyber/index.jsp

  27. Science Discipline Physics, Chemistry, Biology, etc. Computer Science Hardware/Software Applied Mathematics Numerical Analysis, Modeling, Simulation Computational Science:Interdisciplinary Research and Education In the Room Slide by Kris Stewart, EdCenter, San Diego State University

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