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Offer for Ph.D. position (closed)

Stochastic modeling and identification of gene expression dynamics using fluorescence microscopy data


Modeling the dynamics of gene expression is central in the study of the response of bacteria and other living organisms to various stimuli, and has a natural impact in applications such as control of biochemical industrial processes and drug development. Traditional modeling approaches describe gene expression kinetics at a population level by ODEs. However, there is now convincing evidence that stochasticity is inherent in gene expression and plays a key role in living organisms.

Modern techniques for the observation of gene expression at the single-cell level, such as time-lapse fluorescence microscopy, not only provide evidence for the randomness of the process, but also enable us to infer stochastic gene expression models from in vivo experiments. Despite the attention devoted to the topic in the recent years, many fundamental and practical questions remain open and request further investigation.

This Ph.D. proposal concerns the analysis, development and identification of stochastic models for the dynamics of gene expression in single bacterial cells. The research activity will be carried out within the IBIS group at the INRIA Grenoble - Rhône-Alpes center located in Montbonnot.

The objective of the project is twofold. The first goal is to develop methods and tools for the analysis and the identification of stochastic models of genetic networks. The second goal is to provide new contributions to the biological understanding of the causes and the effects of randomness in gene expression. In particular, the research activity will be driven by and applied to time-lapse single-cell fluorescence microscopy experiments on the expression of cAMP-dependent genes in the enterobacterium Escherichia coli.

In the course of the project several questions will be addressed, most notably :

-  A literature review of the biochemical mechanisms underlying gene expression, the role of stochastic noise in gene regulatory networks, stochastic models of gene expression and their relation with classical ODE models, and methods for the simulation of the stochastic models
-  The identifiability of single-cell stochastic gene expression models
-  The development and application of algorithms for the identification of stochastic gene expression models from time-lapse single-cell fluorescence microscopy experiments
-  The development of a stochastic model of the network controlling carbon starvation response in E. coli and its comparison with ODE models previously developed in the IBIS group
-  The identification of this model from the data and the analysis of the regulatory interactions that produce a stochastic pattern of gene expression

Specific applications of the models, such as simple examples of probabilistic model-based control of cell populations, may also be considered. Due to the large size of the datasets produced by the time-lapse single-cell microscopy experiments, a nontrivial issue that will be addressed in the course of the project is the automated processing of the data.

Experiments will be conducted in collaboration with the experimental lab of Prof. Hans Geiselmann (part of IBIS) at the Université Joseph Fourier in Grenoble. The necessary understanding of the biological system is ensured by relevant research activity conducted by IBIS for several years. In addition to the direct access to experimental data and biological support, the project will also profit from the collaboration of IBIS with a number of national and international research institutions and the participation of the group in various research projects.

Skills and Profile

Interested candidates should have a background in system/control theory, computer science and probability theory. They should have working knowledge of scientific programming tools (e.g., Matlab, Scilab, C, ...) and a strong interest in biological applications. The successful candidate will be working in collaboration with biologists, applied mathematicians and computer scientists in an international environment. Propensity to interdisciplinary research, strong motivation, ability to work in group are necessary and expected.

Some relevant bibliography

-  Paulsson, J. (2005) Models of stochastic gene expression. Phys. Life Rev., 2, 157-175.
-  Blake, W.J. et al. (2003) Noise in eukaryotic gene expression. Nature, 422, 633-637.
-  Rao, C.V. et al. (2002) Control, exploitation and tolerance of intracellular noise. Nature, 420, 231-237.
-  Rosenfeld, N. et al. (2005) Gene regulation at the single-cell level. Science, 307, 1962-1965.
-  Longo, D. and Hasty, J. (2006) Dynamics of single-cell gene expression. Mol. Syst. Biol., 2:64.
-  Cinquemani, E. et al. (2008) Stochastic dynamics of genetic networks : modelling and parameter identification. Bioinformatics, 24(23), 2748-2754.
-  Munsky, B. et al. (2009) Listening to the noise : random fluctuations reveal gene network parameters. Mol. Syst. Biol., 5:318.


This position is offered at the INRIA Grenoble - Rhône-Alpes Research Unit of INRIA, located near Grenoble and Lyon. The Unit includes more than 600 people, within 34 research teams and 10 support services.

Application and additional information

Application deadlines, details of the application procedure and additional information on Ph.D. positions at INRIA (eligibility, duration, salary...) are reported on the INRIA official website

Interested candidates should contact :

Eugenio Cinquemani

Hidde de Jong

Hans Geiselmann

Last modified : 10 march 2010