Stochastic Models for Gene Expression: Volume Growth, Cell Division, Gene Replication and Interactions Between Protein Productions

Date Thursday October 05, 2017 at 4:00 PM
Location 13-105 CHS (Center for the Health Sciences)
Speaker Renaud Dessalles, Ph.D. , Visiting Asst Proj Scientist Department of Biomathematics UCLA
Sponsoring Dept UCLA Biomathematics
Abstract Protein production is the fundamental process by which the genetic information of a cell is synthesized into functional products, the proteins. It is a highly stochastic process, in particular for the bacteria, as it is the realization of a very large number of elementary random events of different nature. Classical models of protein production (like those of Rigney and Schieve (1977) and Berg (1978) represent transcription and translation mechanisms to determine their relative impact on the protein variability. Even if these models are commonly used in the literature, they do not represent many aspects yet possibly impacting the protein variability: for instance, the volume growth, the cell division, the gene replication and the sharing of common resources such as RNA-polymerases and ribosomes in the protein synthesis are not represented. We propose here a series of models that successively integrates all these elements; mathematical analysis and simulations of these models will allow us to determine the variability induced by these different features and to compare them to experimental measures.
Flyer 20171005_Renaud_Dessalles_flyer.pdf