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Multiple graph edit distance: simultaneous topological alignment of multiple protein-protein interaction networks with an evolutionary algorithm

Published: 12 July 2014 Publication History

Abstract

Motivation: We address the problem of multiple protein-protein interaction (PPI) network alignment. Given a set of such networks for different species we might ask how much the network topology is conserved throughout evolution. Solving this problem will help to derive a subset of interactions that is conserved over multiple species thus forming a 'core interactome'. Methods: We model the problem as Topological Multiple one-to-one Network Alignment (TMNA), where we aim to minimize the total Graph Edit Distance (GED) between pairs of the input networks. Here, the GED between two graphs is the number of deleted and inserted edges that are required to make one graph isomorphic to another. By minimizing the GED we indirectly maximize the number of edges that are aligned in multiple networks simultaneously. However, computing an optimal GED value is computationally intractable. We thus propose an evolutionary algorithm and developed a software tool, GEDEVO-M, which is able to align multiple PPI networks using topological information only. We demonstrate the power of our approach by computing a maximal common subnetwork for a set of bacterial and eukaryotic PPI networks. GEDEVO-M thus provides great potential for computing the 'core interactome' of different species. Availability: http://gedevo.mpi-inf.mpg.de/multiple-network-alignment/.

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  1. Multiple graph edit distance: simultaneous topological alignment of multiple protein-protein interaction networks with an evolutionary algorithm

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        cover image ACM Conferences
        GECCO '14: Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation
        July 2014
        1478 pages
        ISBN:9781450326629
        DOI:10.1145/2576768
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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        Publication History

        Published: 12 July 2014

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        Author Tags

        1. evolutionary algorithm
        2. graph edit distance
        3. multiple network alignment
        4. protein-protein interaction networks

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        • Research-article

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        • Cluster of Excellence Multimodal Computing and Interaction (MMCI) and the International Max Planck Research School for Computer Science (IMPRS)

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        GECCO '14
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        GECCO '14: Genetic and Evolutionary Computation Conference
        July 12 - 16, 2014
        BC, Vancouver, Canada

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        GECCO '14 Paper Acceptance Rate 180 of 544 submissions, 33%;
        Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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