Faculty Contact: Stephen Proulx
Concepts: Models reduction, time-scales separation, state aggregation
Datasets: Regulatory networks encoded in Systems Biology Markup Language (SBML)
Abstract: Scalability is a major issue in analyzing and identifying large biological networks. Several approaches have been proposed to simplify the analysis of large biological networks, including exploring the existence of multiple time-scales to replace dynamical models by algebraic relationships, projecting high-dimensional dynamics into lower-dimensional state-spaces, and aggregating large sets of states into meta-states. This project aims at familiarizing students with these approaches in the context of the analysis and system identification of cellular regulatory network.