Mustafa Khammash: Stochastic Gene Expression: Mathematical Modeling, Analysis, and Control

Prof. Dr. Mustafa Hani Khammash
ETH Zürich

Stochastic Gene Expression: Mathematical Modeling, Analysis, and Control

Modeling biochemical reaction networks is key to understanding life at the most basic level. One of the challenges to the analysis and synthesis of genetic networks is that the cellular environment in which these circuits function is abuzz with noise. Cellular noise results in random fluctuations within individual cells and is a source of variability among genetically identical populations. The richness of stochastic phenomena in biology underscores the importance of proper modeling, and analysis of cellular noise. In this talk, we present a stochastic modeling paradigm for gene networks and describe some of the key tools for the modeling and analysis of stochasticity inside living cells. An understanding of the stochastic nature of gene expression leads naturally to developing methods for feedback control of genetic circuits. We describe novel analytical and experimental work that demonstrates how light can be used in combination with single cell measurement technology to achieve precise and robust set point regulation of gene expression in the noisy environment of the living cell.