{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T10:14:33Z","timestamp":1778580873687,"version":"3.51.4"},"reference-count":31,"publisher":"Oxford University Press (OUP)","issue":"20","license":[{"start":{"date-parts":[[2016,10,26]],"date-time":"2016-10-26T00:00:00Z","timestamp":1477440000000},"content-version":"vor","delay-in-days":119,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,10,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Network alignment (NA) aims to find regions of similarities between species\u2019 molecular networks. There exist two NA categories: local (LNA) and global (GNA). LNA finds small highly conserved network regions and produces a many-to-many node mapping. GNA finds large conserved regions and produces a one-to-one node mapping. Given the different outputs of LNA and GNA, when a new NA method is proposed, it is compared against existing methods from the same category. However, both NA categories have the same goal: to allow for transferring functional knowledge from well- to poorly-studied species between conserved network regions. So, which one to choose, LNA or GNA? To answer this, we introduce the first systematic evaluation of the two NA categories.<\/jats:p>\n               <jats:p>Results: We introduce new measures of alignment quality that allow for fair comparison of the different LNA and GNA outputs, as such measures do not exist. We provide user-friendly software for efficient alignment evaluation that implements the new and existing measures. We evaluate prominent LNA and GNA methods on synthetic and real-world biological networks. We study the effect on alignment quality of using different interaction types and confidence levels. We find that the superiority of one NA category over the other is context-dependent. Further, when we contrast LNA and GNA in the application of learning novel protein functional knowledge, the two produce very different predictions, indicating their complementarity. Our results and software provide guidelines for future NA method development and evaluation.<\/jats:p>\n               <jats:p>Availability and implementation: Software: http:\/\/www.nd.edu\/~cone\/LNA_GNA<\/jats:p>\n               <jats:p>Contact: tmilenko@nd.edu<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btw348","type":"journal-article","created":{"date-parts":[[2016,6,30]],"date-time":"2016-06-30T01:40:11Z","timestamp":1467250811000},"page":"3155-3164","source":"Crossref","is-referenced-by-count":59,"title":["Local versus global biological network alignment"],"prefix":"10.1093","volume":"32","author":[{"given":"Lei","family":"Meng","sequence":"first","affiliation":[{"name":"1 Department of Computer Science and Engineering"},{"name":"2 ECK Institute of Global Health and Interdisciplinary Center for Network Science and Applications"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aaron","family":"Striegel","sequence":"additional","affiliation":[{"name":"1 Department of Computer Science and Engineering"},{"name":"3 Wireless Institute, University of Notre Dame, Notre Dame, IN 46556, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tijana","family":"Milenkovi\u0107","sequence":"additional","affiliation":[{"name":"1 Department of Computer Science and Engineering"},{"name":"2 ECK Institute of Global Health and Interdisciplinary Center for Network Science and Applications"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2016,6,29]]},"reference":[{"key":"2023020113460190800_btw348-B1","doi-asserted-by":"crossref","first-page":"D637","DOI":"10.1093\/nar\/gkm1001","article-title":"The BioGRID interaction database: 2008 update","volume":"36","author":"Breitkreutz","year":"2008","journal-title":"Nucleic Acids Res"},{"key":"2023020113460190800_btw348-B2","doi-asserted-by":"crossref","first-page":"R95","DOI":"10.1186\/gb-2007-8-5-r95","article-title":"Unequal evolutionary conservation of human protein interactions in interologous networks","volume":"8","author":"Brown","year":"2007","journal-title":"Genome Biol"},{"key":"2023020113460190800_btw348-B3","doi-asserted-by":"crossref","first-page":"e38107","DOI":"10.1371\/journal.pone.0038107","article-title":"AlignNemo: a local network alignment method to integrate homology and topology","volume":"7","author":"Ciriello","year":"2012","journal-title":"Plos One"},{"key":"2023020113460190800_btw348-B4","doi-asserted-by":"crossref","first-page":"2351","DOI":"10.1093\/bioinformatics\/btu307","article-title":"A comparison of algorithms for the pairwise alignment of biological networks","volume":"30","author":"Clark","year":"2014","journal-title":"Bioinformatics"},{"key":"2023020113460190800_btw348-B5","doi-asserted-by":"crossref","first-page":"1988","DOI":"10.1093\/bioinformatics\/btv063","article-title":"A multiobjective memetic algorithm for PPI network alignment","volume":"31","author":"Clark","year":"2015","journal-title":"Bioinformatics"},{"key":"2023020113460190800_btw348-B6","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1074\/mcp.M600381-MCP200","article-title":"Toward a comprehensive atlas of the physical interactome of Saccharomyces cerevisiae","volume":"6","author":"Collins","year":"2007","journal-title":"Mol. 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