{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T05:06:11Z","timestamp":1792213571499,"version":"4.4.0"},"reference-count":23,"publisher":"National Academy of Sciences","issue":"35","content-domain":{"domain":["www.pnas.org"],"crossmark-restriction":true},"short-container-title":["Proc. Natl. Acad. Sci. U.S.A."],"published-print":{"date-parts":[[2008,9,2]]},"abstract":"<jats:p>\n                    Protein\u2013protein interactions (PPIs) and their networks play a central role in all biological processes. Akin to the complete sequencing of genomes and their comparative analysis, complete descriptions of interactomes and their comparative analysis is fundamental to a deeper understanding of biological processes. A first step in such an analysis is to align two or more PPI networks. Here, we introduce an algorithm, IsoRank, for global alignment of multiple PPI networks. The guiding intuition here is that a protein in one PPI network is a good match for a protein in another network if their respective sequences and neighborhood topologies are a good match. We encode this intuition as an eigenvalue problem in a manner analogous to Google's PageRank method. Using IsoRank, we compute a global alignment of the\n                    <jats:italic>Saccharomyces cerevisiae<\/jats:italic>\n                    ,\n                    <jats:italic>Drosophila melanogaster<\/jats:italic>\n                    ,\n                    <jats:italic>Caenorhabditis elegans<\/jats:italic>\n                    ,\n                    <jats:italic>Mus musculus<\/jats:italic>\n                    , and\n                    <jats:italic>Homo sapiens<\/jats:italic>\n                    PPI networks. We demonstrate that incorporating PPI data in ortholog prediction results in improvements over existing sequence-only approaches and over predictions from local alignments of the yeast and fly networks. Previous methods have been effective at identifying conserved, localized network patterns across pairs of networks. This work takes the further step of performing a global alignment of multiple PPI networks. It simultaneously uses sequence similarity and network data and, unlike previous approaches, explicitly models the tradeoff inherent in combining them. We expect IsoRank\u2014with its simultaneous handling of node similarity and network similarity\u2014to be applicable across many scientific domains.\n                  <\/jats:p>","DOI":"10.1073\/pnas.0806627105","type":"journal-article","created":{"date-parts":[[2008,8,25]],"date-time":"2008-08-25T21:09:32Z","timestamp":1219698572000},"page":"12763-12768","update-policy":"https:\/\/doi.org\/10.1073\/pnas.cm10313","source":"Crossref","is-referenced-by-count":528,"title":["Global alignment of multiple protein interaction networks with application to functional orthology detection"],"prefix":"10.1073","volume":"105","author":[{"given":"Rohit","family":"Singh","sequence":"first","affiliation":[{"name":"*Computer Science and Artificial Intelligence Laboratory and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinbo","family":"Xu","sequence":"additional","affiliation":[{"name":"Toyota Technological Institute at Chicago, Chicago, IL 60637"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bonnie","family":"Berger","sequence":"additional","affiliation":[{"name":"*Computer Science and Artificial Intelligence Laboratory and"},{"name":"Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139; and"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"341","published-online":{"date-parts":[[2008,9,2]]},"reference":[{"key":"e_1_3_4_1_2","doi-asserted-by":"publisher","DOI":"10.1038\/35001009"},{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.061034498"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.1038\/nature04670"},{"key":"e_1_3_4_4_2","doi-asserted-by":"publisher","DOI":"10.1038\/nature02555"},{"key":"e_1_3_4_5_2","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bti1054"},{"key":"e_1_3_4_6_2","doi-asserted-by":"publisher","DOI":"10.1002\/pmic.200300636"},{"key":"e_1_3_4_7_2","doi-asserted-by":"publisher","DOI":"10.1101\/gr.5235706"},{"key":"e_1_3_4_8_2","first-page":"187","article-title":"Herpesviral protein networks and their interaction with the human proteome","volume":"311","author":"Uetz P","year":"2005","unstructured":"P Uetz, et al., Herpesviral protein networks and their interaction with the human proteome. Science 311, 187\u2013188 (2005).","journal-title":"Science"},{"key":"e_1_3_4_9_2","doi-asserted-by":"publisher","DOI":"10.1101\/gr.4526006"},{"key":"e_1_3_4_10_2","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkh411"},{"key":"e_1_3_4_11_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1534710100"},{"key":"e_1_3_4_12_2","first-page":"48","article-title":"Pairwise local alignment of protein interaction networks guided by models of evolution","volume":"3500","author":"Koyuturk M","year":"2005","unstructured":"M Koyuturk, A Grama, W Szpankowski, Pairwise local alignment of protein interaction networks guided by models of evolution. RECOMB 3500, 48\u201365 (2005).","journal-title":"RECOMB"},{"key":"e_1_3_4_13_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0602294103"},{"key":"e_1_3_4_14_2","doi-asserted-by":"crossref","unstructured":"M Leordeanu M Hebert A spectral technique for correspondence problems using pairwise constraints.  (IEEE Washington DC) Vol. 2 1482\u20131489 (2005).","DOI":"10.1109\/ICCV.2005.20"},{"key":"e_1_3_4_15_2","first-page":"313","volume-title":"The Neural Information Processing System","author":"Cour T","year":"2006","unstructured":"T Cour, P Srinivasan, J Shi, Balanced spectral matching. The Neural Information Processing System (Neural Information Processing Systems Foundation, La Jolla), pp. 313\u2013320 (2006)."},{"key":"e_1_3_4_16_2","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gki107"},{"key":"e_1_3_4_17_2","doi-asserted-by":"publisher","DOI":"10.1089\/1066527041410319"},{"key":"e_1_3_4_18_2","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-4-41"},{"key":"e_1_3_4_19_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.278.5338.631"},{"key":"e_1_3_4_20_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0000383"},{"key":"e_1_3_4_21_2","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btg1026"},{"key":"e_1_3_4_22_2","doi-asserted-by":"publisher","DOI":"10.1038\/nbt1206-1474"},{"key":"e_1_3_4_23_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0307326101"}],"container-title":["Proceedings of the National Academy of Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pnas.org\/doi\/pdf\/10.1073\/pnas.0806627105","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,12]],"date-time":"2022-04-12T17:15:27Z","timestamp":1649783727000},"score":1,"resource":{"primary":{"URL":"https:\/\/pnas.org\/doi\/full\/10.1073\/pnas.0806627105"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2008,9,2]]},"references-count":23,"journal-issue":{"issue":"35","published-print":{"date-parts":[[2008,9,2]]}},"alternative-id":["10.1073\/pnas.0806627105"],"URL":"https:\/\/doi.org\/10.1073\/pnas.0806627105","relation":{},"ISSN":["0027-8424","1091-6490"],"issn-type":[{"value":"0027-8424","type":"print"},{"value":"1091-6490","type":"electronic"}],"subject":[],"published":{"date-parts":[[2008,9,2]]},"assertion":[{"value":"2008-03-12","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2008-09-02","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}