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Ph-D thesis defended in 2013


Four thesis were defended within the Dyliss team in 2013, on several subjects and applications.

  • Oumarou Abdou Arbi studied the variability of flux distribution within a metabolic network and its application to diary cows. This was a collaboration with the Pegase laboratory of INRA. [thesis]
  • Geoffroy Andrieux studied discrete temporal dynamics of signalling network and their application to TGFbeta pathway. This was a collaboration with the IRSET laboratory from Univ. Rennes 1 and Inserm.
  • Andres Aravena investigated the pruning of regulatory networks and its application to mining bacteria. This was a collaboration with the CMM at universidad de Chile [thesis]
  • Charles Bettembourg introduced semantic methods for comparing metabolic pathways and their application to chicken. This was a collaboration with the Pegase laboratory of INRA.


Mining bacteria

A. ferrooxidans is a bacteria involved in cooper bio-leaching. It is capable of surviving in extreme environment such as mines. It is a typical example of a non-modeled species with interesting economical features. Nonetheless, elucidating the capability of A. Ferroxidans to survive in mines or to decompose copper ore is far from trivial, mainly because this bacteria still cannot be genetically perturbed. The Dyliss team has a long term collaboration with the Center of Mathematical Modelling in Santiago de Chile to use this example as a case-study for developing integrative methods aiming to identify the key regulators of the response to an environmental pertubation. This collaboration is funded by the CIRIC cooperation program from Inria and the Chilean Corfo institution. The thesis of A. Aravena was dedicated to this thema. So was the post-doc of S. Thiele. [know more : the integrativebiochile associated team] [know more: an ASP encoding for the identification of regulation unit in non-model species]


Event Transition Graphs: Markov models for cell dynamics

Ordinary differential equations are currently the most widely used method to model the average dynamics of cells but they require too much information about the system : complete list of reactions, types of kinetic laws and numerous kinetic parameters. In Dyliss team we investigate more abstract semi-quantitative models to deal with this lack of knowledge. The cell dynamics is viewed as a succession of events which are modeled using a Markovian Event Transition Graph. The parameters of our probabilistic model are inferred from steady-state data using asymptotic results on Markov chains inspired from the average-case analysis of algorithms. The model can then be used to simulate cell dynamics, to validate models or to rank reactions according to their sensibility. Our approach is successful in modeling the carbon starvation system of E. Coli. The PhD thesis of V. Picard is dedicated to this thema. [know more: integrating quantitative knowledge into a qualitative gene regulatory network] [know more: The POGG software environment]


Sea Urchin

Dyliss team is in close collaboration with Roscoff Marine Biological Station. We work together on differential and probabilistic models to understand the initiation of the cap-dependant translation in the egg cells of sea urchins. In other words, we study an important mechanism that synthesizes proteins from messenger RNA during the very first minutes of eukaryotic life. This work is a step toward the understanding of eukaryotic translation regulation networks. The PhD students V. Picard and S. Prigent work on this project.[know more : the Roscoff associated team] [know more:Model of cap-dependent translation initiation in sea urchin: A step towards the eukaryotic translation regulation network]