Qualitative analysis of the relation between DNA microarray data and behavioral models of regulation networks

Anne Siegel 1 Ovidiu Radulescu 1, 2, * Michel Le Borgne 1 Philippe Veber 1 Julien Ouy 3 Sandrine Lagarrigue 4
* Corresponding author
1 SYMBIOSE - Biological systems and models, bioinformatics and sequences
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
3 ESPRESSO - Synchronous programming for the trusted component-based engineering of embedded systems and mission-critical systems
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : We introduce a mathematical framework that allows to test the compatibility between differential data and knowledge on genetic and metabolic interactions. Within this framework a behavioral model is represented by a labeled oriented interaction graph; its predictions can be compared to experimental data. The comparison is qualitative and relies on a system of linear qualitative equations derived from the interaction graph. We show how to partially solve the qualitative system, how to identify incompatibilities between the model and the data, and how to detect competitions in the biological processes that are modeled. This approach can be used for the analysis of transcriptomic, metabolic or proteomic data.
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Anne Siegel, Ovidiu Radulescu, Michel Le Borgne, Philippe Veber, Julien Ouy, et al.. Qualitative analysis of the relation between DNA microarray data and behavioral models of regulation networks. BioSystems, Elsevier, 2006, 84, pp.153-174. ⟨inria-00178809⟩

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