Selected publications at LSV

Abstract:
Attractors of network dynamics represent the long-term behaviours of the modelled system. Their characterization is therefore crucial for understanding the response and differentiation capabilities of a dynamical system. In the scope of qualitative models of interaction networks, the computation of attractors reachable from a given state of the network faces combinatorial issues due to the state space explosion. In this paper, we present a new algorithm that exploits the concurrency between transitions of parallel acting components in order to reduce the search space. The algorithm relies on Petri net unfoldings that can be used to compute a compact representation of the dynamics. We illustrate the applicability of the algorithm with Petri net models of cell signalling and regulation networks, Boolean and multi-valued. The proposed approach aims at being complementary to existing methods for deriving the attractors of Boolean models, while being generic since they apply to any safe Petri net.

@inproceedings{CHJPS-cmsb14,
   address = {Manchester, UK},
   author = {Chatain, {\relax Th}omas and Haar, Stefan and Jezequel, Lo{\"\i}g and Paulev{\'e}, Lo{\"\i}c and Schwoon, Stefan},
   booktitle = {{P}roceedings of the 12th {C}onference on {C}omputational {M}ethods in {S}ystem {B}iology ({CMSB}'14)},
   DOI = {10.1007/978-3-319-12982-2_10},
   editor = {Mendes, Pedro},
   month = nov,
   pages = {129-142},
   publisher = {Springer-Verlag},
   series = {Lecture Notes in Bioinformatics},
   title = {Characterization of Reachable Attractors Using {P}etri Net Unfoldings},
   url = {http://www.lsv.ens-cachan.fr/Publis/PAPERS/PDF/CHJPS-cmsb14.pdf},
   volume = {8859},
   year = {2014},
}

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