Global alignment of protein-protein interaction networks by graph matching methods
Mikhail Zaslavskiy (CMM, CB), Francis Bach (CMM, INRIA Rocquencourt),, Jean-Philippe Vert (CB, CBIO)

TL;DR
This paper reformulates the problem of aligning protein-protein interaction networks across species as a graph matching task, proposing new algorithms that outperform existing methods in identifying conserved interactions.
Contribution
It introduces novel graph matching-based methods for PPI network alignment, addressing both strict and flexible matching constraints, and demonstrates superior performance over state-of-the-art algorithms.
Findings
New methods outperform existing algorithms in conserved interaction detection.
Achieved 78% more conserved interactions than IsoRank at similar sequence similarity levels.
Validated on yeast and fly PPI networks.
Abstract
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. 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…
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Taxonomy
TopicsBioinformatics and Genomic Networks · Microbial Metabolic Engineering and Bioproduction · Fungal and yeast genetics research
