Modeling, analysis and reduction of biological systems

Stefano Casagranda 1
1 BIOCORE - Biological control of artificial ecosystems
INRA - Institut National de la Recherche Agronomique, CRISAM - Inria Sophia Antipolis - Méditerranée , LOV - Laboratoire d'océanographie de Villefranche
Abstract : This thesis deals with modeling, analysis and reduction of various biological models, with a focus on gene regulatory networks in the bacterium E. coli. Different mathematical approaches are used. In the first part of the thesis, we model, analyze and reduce, using classical tools, a high-dimensional transcription-translation model of RNA polymerase in E. coli. In the second part, we introduce a novel method called Principal Process Analysis (PPA) that allows the analysis of high-dimensional models, by decomposing them into biologically meaningful processes, whose activity or inactivity is evaluated during the time evolution of the system. Exclusion of processes that are always inactive, and inactive in one or several time windows, allows to reduce the complex dynamics of the model to its core mechanisms. The method is applied to models of circadian clock, endocrine toxicology and signaling pathway; its robustness with respect to variations of the initial conditions and parameter values is also tested. In the third part, we present an ODE model of the gene expression machinery of E. coli cells, whose growth is controlled by an external inducer acting on the synthesis of RNA polymerase. We describe our contribution to the design of the model and analyze with PPA the core mechanisms of the regulatory network. In the last part, we specifically model the response of RNA polymerase to the addition of external inducer and estimate model parameters from single-cell data. We discuss the importance of considering cell-to-cell variability for modeling this process: we show that the mean of single-cell fits represents the observed average data better than an average-cell fit.
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Stefano Casagranda. Modeling, analysis and reduction of biological systems. Other. Université Côte d'Azur, 2017. English. ⟨NNT : 2017AZUR4049⟩. ⟨tel-02169197⟩

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