Section: New Results

Asymptotic dynamics

Participants : Anne Siegel [contact] , Oumarou Abdou-Arbi, Geoffroy Andrieux, Pierre Blavy, Jérémie Bourdon, Damien Eveillard, Michel Le Borgne, Vincent Picard, Sven Thiele, Santiago Videla.

• Probabilistic sources for sequences and systems biology [J. Bourdon] The habilitation thesis surveys how methods based on average-case analysis of algorithms can be used to model the quantitative response of a biological system from a biomolecular to a physiological scale [28] .

• Learning the early-response of protein signaling networks. [S. Videla, S. Thiele, A. Siegel] We demonstrated the usefulness of the Answer Set Programming approach (ASP) to learn Boolean models from high-throughput phospho-proteomics data. Exact constraint solving showed a quantum leap over heuristic (state-of-the-art) methods in terms of efficiency and scalability, and guarantees global optimality of solutions as well as provides a complete set of solutions [19] [Online publication]

• Numerical model of signaling pathways [G. Andrieux, M. Le Borgne] We have proposed an integrative numerical (ODE) model for the dynamic regulation of $TGF\beta$ Signaling by $TIF1\gamma$. The model successfully unifies the seemingly opposite roles of $TIF1\gamma$, and reveals how changing $TIF1\gamma /Smad4$ ratios affect the cellular response to stimulation by $TGF\beta$, accounting for a highly graded determination of cell fate. [10] .

• Identification of regulatory networks in ecology [D. Eveillard] A clustering data-based approach emphasizes regulatory networks at the bacterial population scale. It allowed the identification of antagonistic interactions between heterotrophic bacteria as a potential regulator of community structure of hypersaline microbial mats. [15] [Online publication]