Beams: Backbone Extraction and Merge Strategy for the Global Many-To Alignment of Multiple Ppi Networks

dc.contributor.author Alkan, Ferhat
dc.contributor.author Erten, Cesim
dc.contributor.author Erten, Cesim
dc.date.accessioned 2019-06-27T08:03:02Z
dc.date.available 2019-06-27T08:03:02Z
dc.date.issued 2014
dc.department Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü en_US
dc.description.abstract Motivation: Global many-to-many alignment of biological networks has been a central problem in comparative biological network studies. Given a set of biological interaction networks the informal goal is to group together related nodes. For the case of protein-protein interaction networks such groups are expected to form clusters of functionally orthologous proteins. Construction of such clusters for networks from different species may prove useful in determining evolutionary relationships in predicting the functions of proteins with unknown functions and in verifying those with estimated functions. Results: A central informal objective in constructing clusters of orthologous proteins is to guarantee that each cluster is composed of members with high homological similarity usually determined via sequence similarities and that the interactions of the proteins involved in the same cluster are conserved across the input networks. We provide a formal definition of the global many-to-many alignment of multiple protein-protein interaction networks that captures this informal objective. We show the computational intractability of the suggested definition. We provide a heuristic method based on backbone extraction and merge strategy (BEAMS) for the problem. We finally show through experiments based on biological significance tests that the proposed BEAMS algorithm performs better than the state-of-the-art approaches. Furthermore the computational burden of the BEAMS algorithm in terms of execution speed and memory requirements is more reasonable than the competing algorithms. en_US]
dc.identifier.citationcount 54
dc.identifier.doi 10.1093/bioinformatics/btt713 en_US
dc.identifier.endpage 539
dc.identifier.issn 1367-4803 en_US
dc.identifier.issn 1460-2059 en_US
dc.identifier.issn 1367-4803
dc.identifier.issn 1460-2059
dc.identifier.issue 4
dc.identifier.pmid 24336414 en_US
dc.identifier.scopus 2-s2.0-84894559216 en_US
dc.identifier.startpage 531 en_US
dc.identifier.uri https://hdl.handle.net/20.500.12469/728
dc.identifier.uri https://doi.org/10.1093/bioinformatics/btt713
dc.identifier.volume 30 en_US
dc.identifier.wos WOS:000332032100011 en_US
dc.identifier.wosquality Q1
dc.institutionauthor Alkan, Ferhat en_US
dc.institutionauthor Erten, Cesim en_US
dc.language.iso en en_US
dc.publisher Oxford University Press en_US
dc.relation.journal Bioinformatics en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.scopus.citedbyCount 64
dc.title Beams: Backbone Extraction and Merge Strategy for the Global Many-To Alignment of Multiple Ppi Networks en_US
dc.type Article en_US
dc.wos.citedbyCount 56
dspace.entity.type Publication
relation.isAuthorOfPublication ba94d962-58f9-4c10-bdc8-667be0ec3b67
relation.isAuthorOfPublication.latestForDiscovery ba94d962-58f9-4c10-bdc8-667be0ec3b67

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