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BioSPICE and Problem-Solving Environments for Systems Biology Clifford A. Shaffer Department of Computer Science Virginia Tech Systems Biology • Focus on regulatory mechanisms for biochemical networks – Start with a wiring diagram • Some example problems: – Cell Cycle – Circadian Rhythms Sister chromatid separation Budding SBF Cln2 Unaligned Xsomes Cln3 and Cdh1 Clb2 Mitosis Sic1 Clb2 Bck2 Clb5 Clb2 Cdc20 Cdc20 Mcm1 Cdh1 Clb2 Cdc20 Swi5 P Sic1 Cln2 Sic1 Clb5 Cdc20 MBF Clb? Clb5 DNA synthesis Sic1 SCF d[Cln2] k1 k1' [SBF] k2 [Cln2] dt synthesis degradation d[Clb2] k3 k3' [Mcm1] k4 k4' [Cdh1] [Clb2] k5 [Sic1][Clb2] dt synthesis d[Cdh1] k dt binding degradation ' k 6 6 [Cdc20] [Cdh1]T [Cdh1] J 6 [Cdh1]T [Cdh1] activation k ' k 7 7 [Clb5] [Cdh1] J 7 [Cdh1] inactivation Simulation of the budding yeast cell cycle 2 mass 1 1 . 0 Sic1 Cln2 0 . 5 0 . 0 G1 1 . 5 Cdh1 1 . 0 0 . 5 S/M Clb2 0 . 5 Cdc20 0 . 0 0 . 0 0 5 0 1 0 0 Time (min) 1 5 0 Usage Scenario Data Notebook Experimental Databases Wiring Diagram Differential Equations Analysis Parameter Values Simulation Comparator Data Notebook The Cell (Modeler) Cycle • Outer Loop: – Define Reaction Equations • Inner Loop: – Adjust parameters, initial conditions 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 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 Tools • Specifications for defining models (markup languages) • “Electronic Lab Notebooks” and access to literature, experiments, etc. • User interface for specifying models, parameters, initial conditions • Automated parameter estimation (calibration) • Analysis tools for comparing simulation results and experimental results • Database support for simulations (data mining) 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