The modeling framework is a major component of the Virtual Cell distributed software system. The goal of the modeling framework is to provide the biological abstractions necessary to represent models of cellular physiology. This framework, in turn, uses the services of the Mathematics Framework for the simulation of its models.
System Level Interface
Modeling Language
A declarative modeling language has been developed to concisely describe a class of physiological models that has been encountered in the Virtual Cell project. This language defines molecular species, cellular structures, biochemical reactions, and cellular geometry.
Testability
A substantial advantage of separating the
math framework from the modeling framework is the improved ability to verify the correctness of the two frameworks from high level system interfaces. The Modeling Framework can be tested by specifying simple physiological models, requesting a specific simulation, and observing the resulting mathematical description generated.
Framework Design
The current
implementation of the cell model description involves the
manipulation of abstract modeling objects that reside in the
Modeling Framework as Java objects. These modeling objects can be
edited, viewed, stored in a remote database, and analyzed using the
WWW-based user interface (see
User Interface section). These objects are categorized as
Physiological Models, Geometry, and Application objects. This adopts the naming
convention used in the current Modeling Framework software.
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1. Physiological Models A Model object represents the physiological model of the cell system under study. Each Model is defined as a collection of Species (e.g. calcium, ATP), Reactions (e.g. enzyme kinetics, receptor binding, membrane fluxes), and Structures (e.g. ER, cytosol). |
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2. Cellular Geometry |
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3. Application |
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Structure Mapping The design of the biological to mathematical mapping allows separate use of biology and math interfaces. Simulations may be based upon single point approximation or spatially resolved models. A compartmental model is assumed for a single point approximation. All cellular structures defining the geometry are mapped to a single compartment. A compartmental model can be Deterministic or Stochastic. In a deterministic model, ordinary differential equations representing the reactions kinetics are generated and passed to an interpreted ODE solver within the client application. A stochastic model simulates individual stochastic trajectories as well as probability distributions for species copy numbers. In a spatial model, partial differential equations that correspond to diffusive species, and ODEs for non-diffusive species are generated for the solution of a complete spatial simulation. Each mutually exclusive volumetric region in the geometry is mapped to a single compartment. A compartment that is not spatially resolved in the geometry may be considered continuously distributed within the geometric region of its parent compartment. The simulation is executed on a remote server and the results are displayed in the client application.
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Model Analysis It is important to determine the sensitivity of model behavior to the choice of which physiological mechanisms are incorporated and their parameter values. It is informative to determine the relative change in model behavior due to a relative change in parameter value. For compartmental models, the software computes the sensitivity of any species concentration to any parameter as a function of time evaluated at the nominal solution.

| Technology | Modeling Process | ||
| Software Architecture | Modeling Framework | ||
| Math Framework | User Interface | ||
| Testing Framework | VCML Specification |