The DARPA BioSPICE Project Clifford A. Shaffer Department of Computer Science Virginia Tech
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Transcript of 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
Computer Science: Cliff Shaffer, Layne Watson, Naren Ramakrishnan, Marc Vass, Nick Allen, Jason Zwolak, Dan Mosia, Sumit Shah, Mohsen Ghomi
Comments on Collaboration
Domain team routinely underestimates how difficult it is to create reliable and usable software.
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 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 Modeling
• Focus on regulatory mechanisms for biochemical networks– Start with a wiring diagram
Cln3
Mass
Budding
Cln2SBF
Bck2
and
Clb5MBF
DNA synthesisClb?
SCFP Sic1
Cln2
Sic1
Sic1 Clb5
Swi5
Sister chromatid separation
Unaligned Xsomes
Cdc20 Cdc20Clb5Clb2
Cdh1
Cdh1
Clb2Cdc20
Cdc20
Sic1 Clb2
Clb2Mcm1
Mitosis
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
'1 1 2
d[Cln2][SBF] [Cln2]
dk k k
t
' '3 3 4 4 5
d[Clb2][Mcm1] [Cdh1] [Clb2] [Sic1][Clb2]
dk k k k k
t
' '6 6 T 7 7
6 T 7
[Cdc20] [Cdh1] [Cdh1] [Clb5] [Cdh1]d[Cdh1]
d [Cdh1] [Cdh1] [Cdh1]
k k k k
t J J
synthesis degradation
synthesis degradation binding
activation inactivation
0 50 100 150
0.0
0.5
1.0
1.5
0.0
0.5
0.0
0.5
1.0
1
2
Time (min)
Sic1
mass
Clb2
Cln2
Cdh1
Simulation of the budding yeast cell cycle
G1 S/M
Cdc20
Usage ScenarioUsage Scenario
Data NotebookData Notebook
Wiring DiagramWiring Diagram
Differential EquationsDifferential Equations Parameter ValuesParameter Values
AnalysisAnalysis SimulationSimulation
ComparatorComparator
Data NotebookData Notebook
ExperimentalExperimentalDatabasesDatabases
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
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
• 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 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 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
• 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• 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.)
• 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
• Model Builder
• Run Manager
• Comparator
• Plotter
• Parameter Estimation
• Database support