CAREER:Stochastic Modeling, Analysis and Simulation of Gene Networks

University Of Miami, Coral Gables FL

Investigators

Abstract

A central theme in post-genomic research is the dissection and understanding of the complex dynamical interaction involved in gene regulation. Recent advances in technology have enabled biologists to investigate gene expression and regulation in single cells on a whole-genome scale, which reveals that the amount of mRNA and protein expressed from a gene is a stochastic process. While such experimental studies have provided valuable insights on gene regulation, a computational approach based on stochastic methods is essential to understanding dynamic gene interaction, since intuitive interpretations from experimental results cannot fully expose the dynamics of a gene network. However, the current stochastic approach does not provide sophisticated modeling techniques, analytical methods and efficient simulation algorithms. This research employs a module-based approach to modeling large gene networks, similar to that used in analyzing electronic circuits, and aims to develop computational tools for analyzing and simulating gene networks. The investigator pursues the following three research thrusts: 1) derive a general stochastic model for gene expression and statistical methods for estimating model parameters based on experimental results, 2) characterize some common modules in gene networks and develop a module-based approach to analyzing gene networks, and 3) devise efficient stochastic simulation methods for large gene networks. The computational approach employed in this project will potentially have major impact on biological research, since it will shed light on many unanswered questions related to the stochasticity in gene regulation. The computational tools developed in this project will find numerous applications in biological research related to the design of drugs and synthetic gene circuits, as well as the investigation of diseases, such as cancer. The methods devised in this research can also be employed to simulate communication networks and design or optimize network protocols.