Modeling the Cell Cycle with JigCell and DARPA’s BioSPICE Software Departments of Computer...
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Transcript of Modeling the Cell Cycle with JigCell and DARPA’s BioSPICE Software Departments of Computer...
Modeling the Cell Cycle with JigCell and DARPA’s BioSPICE Software
Departments of Computer Science* and Biology+,Virginia Tech
Blacksburg, VA 24061
Faculty:Kathy Chen+
Cliff Shaffer*
John Tyson+
Layne Watson*
Students:Nick Allen*
Emery Conrad+
Ranjit Randhawa*
Marc Vass*
Jason Zwolak*
The Fundamental Goal of Molecular Cell Biology
Application:Cell Cycle Modeling
How do cells convert genes into behavior? Create proteins from genes Protein interactions Protein effects on the cell
Our study organism is the cell cycle of the budding yeast Saccharomyces cerevisiae.
mitosis(M phase)
DNA replication(S phase)
cell division
G1
G2
Modeling Techniques
We use ODEs that describe the rate at which each protein concentration changes Protein A degrades protein B:
… with initial condition [A](0) = A0.
Parameter c determines the rate of degradation.
]A[]B[
cdt
d
Modeling Lifecycle
Data NotebookData Notebook
Wiring DiagramWiring Diagram
Differential EquationsDifferential Equations Parameter ValuesParameter Values
AnalysiAnalysiss
SimulationSimulation
ComparatorComparator
Data NotebookData Notebook
ExperimentalExperimentalDatabasesDatabases
Tyson’s Budding Yeast Model
Tyson’s model contains over 30 ODEs, some nonlinear.
Events can cause concentrations to be reset.
About 140 rate constant parameters Most are unavailable from experiment and must set by
the modeler “Parameter twiddling” Far better is automated parameter estimation
JigCell
Current Primary Software Components:JigCell Model Builder
JigCell Run Manager
JigCell Comparator
Automated Parameter Estimation (PET)
Bifurcation Analysis (Oscill8)
http://jigcell.biol.vt.edu
JigCell Model Builder
(Frogegg model)
Mutations
Wild type cell
Mutations Typically caused by gene knockout Consider a mutant with no B to degrade A.
Set c = 0 We have about 130 mutations
each requires a separate simulation run
JigCell Run Manager
Phenotypes
Each mutant has some observed outcome (“experimental” data). Generally qualitative. Cell lived Cell died in G1 phase
Model should match the experimental data. Model should not be overly sensitive to the rate
constants. Overly sensitive biological systems tend not to
survive
Comparator
BioSPICE
DARPA projectApproximately 15 groupsMany (not all) active systems biology modelers and software developers representedAn explicit integration teamGoal: Define mechanisms for interoperability of software tools, build an expandable problem solving environment for systems biologyResult: software tools contributed by the community to the community
Tools
Specifications for defining models (SBML)Standards for data representation, APIsSimulators (equation solvers; stochastic)Automated parameter estimationAnalysis tools (plotters, bifurcation analysis, flux balance, etc.)Database support for simulations (data mining)