Towards a logic-based method to infer provenance-aware molecular networks

Zahira Aslaoui-Errafi 1, 2 Sarah Cohen-Boulakia 1, 2 Christine Froidevaux 1, 2, * Pauline Gloaguen 3 Anne Poupon 3 Adrien Rougny 1, 2 Meriem Yahiaoui 1, 2
* Corresponding author
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
Abstract : Providing techniques to automatically infer molecular networks is particularly important to understand complex relationships between biological objects. We present a logic-based method to infer such networks and show how it allows inferring signalling networks from the design of a knowledge base. Provenance of inferred data has been carefully collected, allowing quality evaluation. More precisely, our method (i) takes into account various kinds of biological experiments and their origin; (ii) mimics the scientist's reasoning within a first-order logic setting; (iii) specifies precisely the kind of interaction between the molecules; (iv) provides the user with the provenance of each interaction; (v) automatically builds and draws the inferred network.
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Zahira Aslaoui-Errafi, Sarah Cohen-Boulakia, Christine Froidevaux, Pauline Gloaguen, Anne Poupon, et al.. Towards a logic-based method to infer provenance-aware molecular networks. Proc. of the 1st ECML/PKDD International workshop on Learning and Discovery in Symbolic Systems Biology (LDSSB), Sep 2012, Bristol, United Kingdom. pp.103-110. ⟨hal-00748041⟩

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