Global alignment of protein-protein interaction networks by graph matching methods.

Mikhail Zaslavskiy 1, 2 Francis Bach 1, 3 Jean-Philippe Vert 2, 4, *
* Auteur correspondant
3 WILLOW - Models of visual object recognition and scene understanding
DI-ENS - Département d'informatique de l'École normale supérieure, ENS Paris - École normale supérieure - Paris, Inria Paris-Rocquencourt, CNRS - Centre National de la Recherche Scientifique : UMR8548
Abstract : MOTIVATION: Aligning protein-protein interaction (PPI) networks of different species has drawn a considerable interest recently. This problem is important to investigate evolutionary conserved pathways or protein complexes across species, and to help in the identification of functional orthologs through the detection of conserved interactions. It is, however, a difficult combinatorial problem, for which only heuristic methods have been proposed so far. RESULTS: We reformulate the PPI alignment as a graph matching problem, and investigate how state-of-the-art graph matching algorithms can be used for that purpose. We differentiate between two alignment problems, depending on whether strict constraints on protein matches are given, based on sequence similarity, or whether the goal is instead to find an optimal compromise between sequence similarity and interaction conservation in the alignment. We propose new methods for both cases, and assess their performance on the alignment of the yeast and fly PPI networks. The new methods consistently outperform state-of-the-art algorithms, retrieving in particular 78% more conserved interactions than IsoRank for a given level of sequence similarity. AVAILABILITY: All data and codes are freely and publicly available upon request.
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Contributeur : Mikhail Zaslavskiy <>
Soumis le : jeudi 7 mai 2009 - 19:59:21
Dernière modification le : mardi 12 septembre 2017 - 11:41:40
Document(s) archivé(s) le : jeudi 10 juin 2010 - 22:56:00


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Mikhail Zaslavskiy, Francis Bach, Jean-Philippe Vert. Global alignment of protein-protein interaction networks by graph matching methods.. Bioinformatics, Oxford University Press (OUP), 2009, 25 (12), pp.i259-67. <10.1093/bioinformatics/btp196>. <hal-00382501>



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