VCell: an introduction and its capabilities
|Software Architecture||Modeling Framework|
|Math Framework||User Interface|
|Testing Framework||VCML Specificaiton|
VCell primary documents are the BioModel, MathModel, Geometry, Application and Simulation.
BioModel consists of the
- Physiology - conceptual representation of the model: structures, molecules, connectivity map, kinetics.
- One or more Applications - virtual experiments that can be simulated: initial conditions, actual morphologies, electrical protocols, etc.
- An Application can be compartmental or it can use a Geometry (see below).
- Each Application has a mathematical representation that is automatically generated and can be viewed.
- For each Application you can specify one or more
- Simulations (time length, resolution, solvers to use, parameter overrides, etc.) that will run and produce Results. Results can be viewed in VCell or exported to a variety of formats.
MathModel is somewhat equivalent to the math description of a BioModel Application – it is a direct specification of the equations to be solved, using the VCell modeling language. It can be compartmental or it can use a spatial Geometry. One or more Simulations must be defined for each MathModel to run and produce Results.
- The math from a BioModel Application is a valid MathModel, but MathModel can not be extended to a BioModels. MathModels are needed to override biology-driven limitations of BioModels.
Geometry is a representation of a spatial structure which a BioModel Application (or a MathModel) can use for spatially resolved simulation. It can be 1-D, 2-D, or 3-D, and either analytically defined or based on a digital image.
- Forward Euler (First Order, Fixed Time Step)
- Runge-Kutta (Second Order, Fixed Time Step)
- Runge-Kutta (Fourth Order, Fixed Time Step)
- Adams-Moulton (Fifth Order, Fixed Time Step)
- Runge-Kutta-Fehlberg (Fifth Order, Variable Time Step)
- IDA (Variable Order, Variable Time Step, ODE/DAE)
- CVODE (Variable Order, Variable Time Step)
- Combined stiff solver CVODE/IDA
Non-Spatial Deterministic (ODE) Solvers
- Semi-Implicit Finite Volume, Regular Grid (Fixed Time Step)
- Semi-Implicit Finite Volume Compiled, Regular Grid (Fixed Time Step)
- Fully-Implicit Finite Volume, Regular Grid (Fixed Time Step).
Spatial Deterministic (PDE) Solvers
- Gibson (Next Reaction Stochastic Method)
- Hybrid (Gibson + Euler-Matuyama Method)
- Hybrid (Gibson + Milstein Method)
- Hybrid (Adaptive Gibson + Milstein Method)
Non-Spatial Stochastic Solvers
- Smoldyn ("Smoluchowski Dynamics" written by Dr. Steve Andrews)
Spatial Stochastic Solvers
Parameter Estimation using COPASI for Non-Spatial Deterministic Problems(Only available in VCell 5.1 Beta version or later)
The Virtual Cell incorporates the COPASI parameter estimation capabilites to optimize parameters in non-spatial deterministic models to best fit experimental data. The available optmization solvers are listed below:
- Evolutionary Programming
- Evolution Strategy (SRES)
- Genetic Algorithm
- Genetic Algorithm SR
- Hooke and Jeeves
- Levenberg - Marquardt
- Nelder - Mead
- Particle Swarm
- Random Search
- Simulated Annealing
- Steepest Descent
- Truncated Newton
- Comaprtmental volumes and membrane sizes
- Concentrations and/or molecule counts for species
- 3D Diffusion
- 2D Membrane Diffusion
- Advection (Velocity)
- Local and global parameters
- Initial conditions can be specified in terms of other model parameters, reserved symbols and species.
- Creating analytic shapes in geometry editor.
- Protein Subcellular Location Image Database (PSLID) import and data handling in FieldData.
- Allow membrane field data from simulation results.
- Predefined ROIs for existing spatial compartments.
- ROIs from user defined Boolean functions.
- ROIs from user drawn polygons.
- Improved spatial data analysis for ROIs.
- Auto-complete text
- Sort and search in Math Viewer and Math Model editor.
- Links to BioModels.net database
- Basic CellML import into MathModels.
- Formalize VCML as XML document
- Annotations (MIRIAM compliant)
- Create pdf report of models
- Field data (using images data as input to simulations)
- CVODE solver used for Optimization in parameter estimation.
- Parameter scans
- 3D Surface Visualization for spatial simulation results