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Integrating these additional types of data is shown to improve IsoRank's predictions of classes of genes that have sparse coverage in the original protein-interaction networks.","abstract_html":"To more accurately predict which genes from different species have the same function (orthologs), I extend the network-alignment algorithm IsoRank to simultaneously align multiple unrelated networks over the same set of nodes. In addition to the original protein-interaction networks, I align genetic-interaction networks, gene-expression correlations, and chromosome localization data to improve the functional similarity of aligned genes. Alignments are evaluated with consistency measurements of protein function within ortholog clusters, and with an information-retrieval statistic from a small set of known orthologs. Integrating these additional types of data is shown to improve IsoRank's predictions of classes of genes that have sparse coverage in the original protein-interaction networks.","abstract_has_math":false,"creators":["Eisner, Eric David"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["Bonnie Berger."],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011","date_published":"2011","updated_at":"2026-07-22T22:22:27Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 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