CCAM Cellular Modeling
Analysis and Simulation
Cowan, Moraru, Schaff
Complex imaging data contains a wealth of quantitative information, but it is often a non-trivial process to extract quantitative parameters from the data. Absolute or relative concentrations of a molecule within the cell, the fraction of molecules that are freely diffusing and their diffusion coefficients, kinetic constants for binding to large complexes, and velocities of directed motion are all parameters that can be obtained from imaging experiments. In most cases, cellular geometries preclude the use of simple analytic solutions to extract the relevant information. Spatial simulations within the same cellular geometry as the experiment provide a tool to determine such quantitative parameters. CCAM is building a suite of software tools specifically geared to these applications.
Data Integration
Moraru, Schaff, Slepchenko
The development of quantitative models of biological processes often requires explicitly accounting for the experimental conditions involved in capturing experimental data. Thus experimental data is not only what is measured but what is used to take such measurements. In order to facilitate researchers' ability to rapidly create quantitative models of cellular physiology, faculty at CCAM are developing the computational technology ncessary to extract and reduce experimental data to standard formats that can be readily input into quantitative computational models. We develop software interfaces to data sources such as immunofluorescence images and Fluorscence Correlation Spectroscopy to derive spatial distributions, intracellular diffusion coefficients, concentrations and interactions. These data linkages require skills in computing and computation to accurately link experimental data directly to computational models.