{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T04:32:23Z","timestamp":1767846743151,"version":"3.49.0"},"reference-count":21,"publisher":"Oxford University Press (OUP)","issue":"16","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2006,8,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Experimental limitations in high-throughput protein\u2013protein interaction detection methods have resulted in low quality interaction datasets that contained sizable fractions of false positives and false negatives. Small-scale, focused experiments are then needed to complement the high-throughput methods to extract true protein interactions. However, the naturally vast interactomes would require much more scalable approaches.<\/jats:p>\n               <jats:p>Results: We describe a novel method called IRAP* as a computational complement for repurification of the highly erroneous experimentally derived protein interactomes. Our method involves an iterative process of removing interactions that are confidently identified as false positives and adding interactions detected as false negatives into the interactomes. Identification of both false positives and false negatives are performed in IRAP* using interaction confidence measures based on network topological metrics. Potential false positives are identified amongst the detected interactions as those with very low computed confidence values, while potential false negatives are discovered as the undetected interactions with high computed confidence values. Our results from applying IRAP* on large-scale interaction datasets generated by the popular yeast-two-hybrid assays for yeast, fruit fly and worm showed that the computationally repurified interaction datasets contained potentially lower fractions of false positive and false negative errors based on functional homogeneity.<\/jats:p>\n               <jats:p>Availability: The confidence indices for PPIs in yeast, fruit fly and worm as computed by our method can be found at our website<\/jats:p>\n               <jats:p>Contact: \u00a0skng@i2r.a-star.edu.sg<\/jats:p>\n               <jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btl335","type":"journal-article","created":{"date-parts":[[2006,6,21]],"date-time":"2006-06-21T03:47:02Z","timestamp":1150861622000},"page":"1998-2004","source":"Crossref","is-referenced-by-count":61,"title":["Increasing confidence of protein interactomes using network topological metrics"],"prefix":"10.1093","volume":"22","author":[{"given":"Jin","family":"Chen","sequence":"first","affiliation":[{"name":"School of Computing, National University of Singapore 1 \u00a0 1 \u00a0 \u00a0 Singapore 119260"},{"name":"Knowledge Discovery Department, Institute for Infocomm Research 2 \u00a0 2 \u00a0 \u00a0 Singapore 119613"}]},{"given":"Wynne","family":"Hsu","sequence":"additional","affiliation":[{"name":"School of Computing, National University of Singapore 1 \u00a0 1 \u00a0 \u00a0 Singapore 119260"}]},{"given":"Mong Li","family":"Lee","sequence":"additional","affiliation":[{"name":"School of Computing, National University of Singapore 1 \u00a0 1 \u00a0 \u00a0 Singapore 119260"}]},{"given":"See-Kiong","family":"Ng","sequence":"additional","affiliation":[{"name":"Knowledge Discovery Department, Institute for Infocomm Research 2 \u00a0 2 \u00a0 \u00a0 Singapore 119613"}]}],"member":"286","published-online":{"date-parts":[[2006,6,20]]},"reference":[{"key":"2023012409112884400_b1","doi-asserted-by":"crossref","first-page":"2026","DOI":"10.1126\/science.1092645","article-title":"Structure-based assembly of protein complexes in yeast","volume":"303","author":"Aloy","year":"2004","journal-title":"Science"},{"key":"2023012409112884400_b2","first-page":"368","article-title":"Systematic assessment of high-throughput experimental data for reliable protein interactions using network topology","author":"Chen","year":"2004"},{"key":"2023012409112884400_b3","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.artmed.2005.02.004","article-title":"Towards discovering reliable protein interactions from high-throughput experimental data using network topology","volume":"35","author":"Chen","year":"2005","journal-title":"Artif. 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