System Identification for Genetic Regulatory Networks

Mary Dunlop, California Institute of Technology

Biological systems rely on complicated regulatory networks to help the organism respond to changing environmental conditions. These genetic regulatory mechanisms can be studied with the same tools that are used to understand regulatory systems that are built by engineers (like the flight control system on an airplane). I will discuss system identification, an engineering tool that we use to help develop better models of genetic regulatory networks. System identification is the process of developing mathematical models of dynamical systems based on experimental observations, so it is well suited to biological experiments, which produce data but lack precise mathematical models. We study genetic regulatory networks both computationally (on my Linux machine) and experimentally (in E. coli bacteria).

Abstract Author(s): Mary J. Dunlop