Download Presentation - JigCell

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
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
Systems Biology: Pathway
Modeling
• Focus on regulatory mechanisms for
biochemical networks
Systems Biology: Pathway
Modeling
• Focus on regulatory mechanisms for
biochemical networks
– Start with a wiring diagram
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
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
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
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.
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
JigCell Model Builder
JigCell Run Manager
JigCell Comparator
Plotter