Subject: Control and optimal control of bacterial growth.
Duration: 12 months
Location: INRIA Sophia-Antipolis (South of France, near Nice)
Contact: Gouze Jean-Luc email@example.com
Santé, biologie et planète numérique
Tags: Gene networks, biological models, control, dynamical systems, computational biology, numerical simulation
The study of genetic regulatory networks has taken a qualitative leap through the use of modern genomic techniques that allow simultaneous measurement of the expression levels of all genes of an organism. In addition to high-throughput experimental methods, approaches in mathematics and computer science will be indispensable for analyzing the dynamics of genetic regulatory networks. BIOCORE team applies mathematical and computational methods from Control Theory and Dynamical Systems to the study of models of genetic networks and more general biological networks (metabolic networks, signaling networks…).
The general goal of this work is to design control strategies for improving product yield and productivity in E coli bacteria.
The Gene Expression Machinery of this bacterium has been modified (by techniques of genetic engineering) to obtain a strain where a chemical inducer controls the expression of RNA polymerase (an enzyme needed for the expression of the genes).
A simplified dynamical model of this controlled GEM will be developed (with our partners) and studied.
We will notably characterize the transients towards steady states and their duration, as well as the
dependence of these properties on the concentrations of nutrients and inducer in the medium. Moreover, the possibility to externally adjust transients by choosing appropriate nutrients and inducer concentrations provides control parameters for, in the first place, the satisfaction of some biological constraints on the
variables and dynamical behavior , and secondly, the optimization of product yield. Using
optimal control, computer simulation and optimization, we will design control laws, possibly including
feedback. The above analysis will also be carried out for fed-batch cultures in a fermenter,
the condition most relevant for industrial biotechnological processes.
The work is done in collaboration with IBIS Inria Team (Grenoble) within the BIO-INFORMATIQUE ANR RESET project (see https://project.inria.fr/reset/).
We are looking for an applied mathematician with a background in the analysis of dynamical systems, and familiar with control theory (and optimal control). In addition, we expect a strong motivation to work on biological applications in genomics.
Web page of JL Gouze http://www-sop.inria.fr/members/Jean-Luc.Gouze/JLGouze-eng.html
Web page of M. Chaves http://www-sop.inria.fr/members/Madalena.Chaves