the darpa biospice project clifford a shaffer department of computer science virginia tech n.
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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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vt team
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

comments on collaboration1
Comments on Collaboration

Domain team routinely underestimates how difficult it is to create reliable and usable software.

comments on collaboration2
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.
comments on collaboration3
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.
systems biology pathway modeling1
Systems Biology: Pathway Modeling
  • Focus on regulatory mechanisms for biochemical networks
systems biology pathway modeling2
Systems Biology: Pathway Modeling
  • Focus on regulatory mechanisms for biochemical networks
    • Start with a wiring diagram
slide10

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

systems biology pathway modeling3
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
slide12

synthesis

synthesis

binding

degradation

degradation

activation

inactivation

slide13

G1

S/M

Simulation of the budding yeast cell cycle

mass

Sic1

Cln2

Clb2

Cdh1

Cdc20

Time (min)

slide14

Experimental

Databases

Usage Scenario

Data Notebook

Wiring Diagram

Differential Equations

Parameter Values

Simulation

Analysis

Comparator

Data Notebook

the cell modeler cycle
The Cell (Modeler) Cycle
  • Outer Loop:
    • Define Reaction Equations
  • Inner Loop:
    • Adjust parameters, initial conditions
fundamental activities
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 modelers1
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
our mission build software to help the modelers2
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
another view
Another View
  • Current models of simple organisms contain a few 10s of equations.
another view1
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.
another view2
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.
another view3
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.
biospice
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
tools
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)
tools cont
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)
jigcell
JigCell
  • Model Builder
  • Run Manager
  • Comparator
  • Plotter
  • Parameter Estimation
  • Database support