{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T14:49:15Z","timestamp":1768315755467,"version":"3.49.0"},"reference-count":25,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":2138,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/2.0\/uk\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: Advanced technologies are producing large-scale protein\u2013protein interaction data at an ever increasing pace. A fundamental challenge in analyzing these data is the inference of protein machineries. Previous methods for detecting protein complexes have been mainly based on analyzing binary protein\u2013protein interaction data, ignoring the more involved co-complex relations obtained from co-immunoprecipitation experiments.<\/jats:p><jats:p>Results: Here, we devise a novel framework for protein complex detection from co-immunoprecipitation data. The framework aims at identifying sets of preys that significantly co-associate with the same set of baits. In application to an array of datasets from yeast, our method identifies thousands of protein complexes. Comparing these complexes to manually curated ones, we show that our method attains very high specificity and sensitivity levels (\u223c 80%), outperforming current approaches for protein complex inference.<\/jats:p><jats:p>Availability: Supplementary information and the program are available at http:\/\/www.cs.tau.ac.il\/~roded\/CODEC\/main.html.<\/jats:p><jats:p>Contact: \u00a0roded@post.tau.ac.il<\/jats:p><jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btq652","type":"journal-article","created":{"date-parts":[[2010,11,27]],"date-time":"2010-11-27T01:19:15Z","timestamp":1290820755000},"page":"111-117","source":"Crossref","is-referenced-by-count":44,"title":["Identification of protein complexes from co-immunoprecipitation data"],"prefix":"10.1093","volume":"27","author":[{"given":"Guy","family":"Geva","sequence":"first","affiliation":[{"name":"School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roded","family":"Sharan","sequence":"additional","affiliation":[{"name":"School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2010,11,25]]},"reference":[{"key":"2023012511161242600_B1","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1016\/S0092-8674(00)80922-8","article-title":"The cell as a collection of protein machines: preparing the next generation of molecular biologists","volume":"92","author":"Alberts","year":"1998","journal-title":"Cell"},{"key":"2023012511161242600_B2","doi-asserted-by":"crossref","first-page":"991","DOI":"10.1038\/nbt1002-991","article-title":"Analyzing yeast protein-protein interaction data obtained from different sources","volume":"20","author":"Bader","year":"2002","journal-title":"Nat. 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