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Translating the SBGN-AF language into logic to analyze signalling networks

Adrien Rougny 1, 2 Christine Froidevaux 1, 2 Yoshitaka Yamamoto 3 Katsumi Inoue 4 
2 AMIB - Algorithms and Models for Integrative Biology
LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau], LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France
4 Inoue Laobratory
NII - National Institute of Informatics
Abstract : Systems Biology focuses on the understanding of complex biological systems as a whole. These systems are often represented in the literature as molecular networks, such as metabolic and signalling networks. With the rise of high-throughput data, automatic methods are needed in order to build and analyze networks that are bigger and bigger. Reasoning techniques seem to be suitable to perform these tasks for three reasons: (i) they do not need any quantitative biological pa- rameters that are often hard to obtain, (ii) the processes that allowed to obtain the results are understandable by the biologist experts and can be explained and (iii) they allow to perform different tasks in the same formal framework. In this paper, we propose a translation into logics of the Systems Biology Graphical Notation Activity Flow language (SBGN- AF), which is a standard graphical notation used to represent molecular networks. We show how this translation can be used to analyze signalling networks with one analysis example.
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Submitted on : Monday, January 6, 2014 - 3:19:25 PM
Last modification on : Tuesday, July 5, 2022 - 8:38:30 AM


  • HAL Id : hal-00924230, version 1



Adrien Rougny, Christine Froidevaux, Yoshitaka Yamamoto, Katsumi Inoue. Translating the SBGN-AF language into logic to analyze signalling networks. LNMR - 1st International Workshop on Learning and Non Monotonic Reasoning, Sep 2013, La Coruña, Spain. pp.44-55. ⟨hal-00924230⟩



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