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The DARPA BioSPICE Project Clifford A. Shaffer Department of Computer Science Virginia Tech

The DARPA BioSPICE Project Clifford A. Shaffer Department of Computer Science Virginia Tech. VT Team. Biology: John Tyson, Jill Sible, Kathy Chen, Laurence Calzone, Emery Conrad, Andrea Ciliberto, Amit Dravid

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The DARPA BioSPICE Project Clifford A. Shaffer Department of Computer Science Virginia Tech

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  1. The DARPA BioSPICE ProjectClifford A. ShafferDepartment of Computer ScienceVirginia Tech

  2. VT Team Biology: John Tyson, Jill Sible, Kathy Chen, Laurence Calzone, Emery Conrad, Andrea Ciliberto, Amit Dravid Computer Science: Cliff Shaffer, Layne Watson, Naren Ramakrishnan, Marc Vass, Nick Allen, Jason Zwolak, Dan Mosia, Sumit Shah, Mohsen Ghomi

  3. Comments on Collaboration

  4. Comments on Collaboration Domain team routinely underestimates how difficult it is to create reliable and usable software.

  5. Comments on Collaboration • Domain team routinely underestimates how difficult it is to create reliable and usable software. • CS team routinely underestimates how difficult it is to stay focussed on the needs of the domain team.

  6. Comments on Collaboration • Domain team routinely underestimates how difficult it is to create reliable and usable software. • CS team routinely underestimates how difficult it is to stay focussed on the needs of the domain team. • Partial solution: truly integrate.

  7. Systems Biology: Pathway Modeling

  8. Systems Biology: Pathway Modeling • Focus on regulatory mechanisms for biochemical networks

  9. Systems Biology: Pathway Modeling • Focus on regulatory mechanisms for biochemical networks • Start with a wiring diagram

  10. Sister chromatid separation Unaligned Xsomes Cdh1 Clb5 Clb2 Cdc20 Cdc20 Mcm1 Clb2 Sic1 Mitosis Clb2 Clb2 Cdc20 Sic1 Sic1 Swi5 P Sic1 Cln2 Clb5 Clb? Budding Cln2 SBF Mass Cdh1 Cln3 and Bck2 SCF Cdc20 MBF Clb5 DNA synthesis

  11. Systems Biology: Pathway Modeling • Focus on regulatory mechanisms for biochemical networks • Start with a wiring diagram • Some example problems: • Cell Cycle (John Tyson) • Circadian Rhythms

  12. synthesis synthesis binding degradation degradation activation inactivation

  13. G1 S/M Simulation of the budding yeast cell cycle mass Sic1 Cln2 Clb2 Cdh1 Cdc20 Time (min)

  14. Experimental Databases Usage Scenario Data Notebook Wiring Diagram Differential Equations Parameter Values Simulation Analysis Comparator Data Notebook

  15. The Cell (Modeler) Cycle • Outer Loop: • Define Reaction Equations • Inner Loop: • Adjust parameters, initial conditions

  16. Fundamental Activities • Collect information • Search literature (databases), Lab notebooks • Define/modify models • A user interface problem • Run simulations • Equation solvers (ODEs, PDEs, deterministic, stochastic) • Compare simulation results to experimental data • Analysis

  17. Our Mission: Build Software to Help the Modelers

  18. Our Mission: Build Software to Help the Modelers • Now: Typical cycle time for changing the model is one month • Collect data on paper lab notebooks • Convert to differential equations by hand • Calibrate the model by trial and error • Inadequate analysis tools

  19. Our Mission: Build Software to Help the Modelers • Now: Typical cycle time for changing the model is one month • Collect data on paper lab notebooks • Convert to differential equations by hand • Calibrate the model by trial and error • Inadequate analysis tools • Goal: Change the model once per day. • Bottleneck should shift to the experimentalists

  20. Another View • Current models of simple organisms contain a few 10s of equations.

  21. Another View • Current models of simple organisms contain a few 10s of equations. • To model mammalian systems might require two orders of magnitude in additional complexity.

  22. Another View • Current models of simple organisms contain a few 10s of equations. • To model mammalian systems might require two orders of magnitude in additional complexity. • We hope our current vision for tools can supply one order of magnitude.

  23. Another View • Current models of simple organisms contain a few 10s of equations. • To model mammalian systems might require two orders of magnitude in additional complexity. • We hope our current vision for tools can supply one order of magnitude. • The other order of magnitude is an open problem.

  24. BioSPICE • DARPA project • Approximately 15 groups • Many (not all) of the systems biology modelers and software developers • An explicit integration team • Goal: Define mechanisms for interoperability of software tools, build an expandable problem solving environment for systems biology • Result: software tools contributed by the community to the community

  25. Tools • Specifications for defining models (markup languages) • “Electronic Lab Notebooks” and access to literature, experiments, etc. • User interface for specifying models, parameters, initial conditions • Simulators (equation solvers)

  26. Tools (cont.) • Automated parameter estimation (calibration) • Analysis tools for comparing simulation results and experimental results • Analysis tools for “higher order” analysis of models (bifurcation analysis) • Database support for simulations (data mining)

  27. JigCell • Model Builder • Run Manager • Comparator • Plotter • Parameter Estimation • Database support

  28. JigCell Model Builder

  29. JigCell Run Manager

  30. JigCell Comparator

  31. Plotter

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