Biocomputation Group
at the University of Pennsylvania


Question or Comment
Contact: Valentina Sokolskaya
Last updated: January 10, 05

Traditionally, modeling and simulation of metabolic and cellular control pathways are based on either continuous or discrete dynamics. Central to our modeling approach is the paradigm of hybrid models in which discrete events are combined with continuous differential equations to capture the switching behavior that is observed in phenomena such as transcription, protein-protein interactions, and cell division and growth. By extension, modeling biological systems as hybrid systems benefits from the rich set of theory and results derived from research in other hybrid systems such as automated highway systems, air-traffic management systems, embedded automotive controllers, manufacturing systems, chemical processes, and robotic control.

Our group brings expertise in modeling, computational, and experimental research at multiple spatio-temporal scales. We have developed a hybrid systems modeling paradigm for genetic networks and hybrid systems analysis tools for predicting behaviors under parameteric and functional uncertainty. We have also developed novel approaches to modeling the interdependency of metabolic and genetic networks by integrating disparate models. Finally, we have developed a software toolset called BioCharon, that integrates modeling and analysis tools for biomolecular networks.