Published 2013
| Version v1
Journal article
Interconnection of asynchronous Boolean networks, asymptotic and transient dynamics
Creators
Contributors
Others:
- Unité Mathématique Informatique et Génome (MIG) ; Institut National de la Recherche Agronomique (INRA)
- Biological control of artificial ecosystems (BIOCORE) ; Laboratoire d'océanographie de Villefranche (LOV) ; Observatoire océanologique de Villefranche-sur-mer (OOVM) ; Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM) ; Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre Inria d'Université Côte d'Azur (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de la Recherche Agronomique (INRA)
Description
The dynamics of the interconnection of two Boolean networks is analyzed directly from the properties of the two individual modules. Motivated by biological systems where multiple timescales are present, we consider asynchronous Boolean networks, whose dynamics can be described by nondeterministic transition graphs. Two new objects are introduced, the asymptotic and the cross graphs, constructed from the strongly connected components of the modules' transition graphs. It is then proved that the asymptotic graph actually recovers the attractors of the interconnected system, while reducing overall computational cost. Illustrated by various biological applications, this method is applied to analyze a composition of several well known modules (multicellular modeling), or to analyze a high dimensional model through its decomposition into smaller input/output subnetworks (model reduction).
Abstract
International audienceAdditional details
Identifiers
- URL
- https://inria.hal.science/hal-00848450
- URN
- urn:oai:HAL:hal-00848450v1
Origin repository
- Origin repository
- UNICA