HIPPIE: Integrating protein interaction networks with experiment based quality scores
Protein function is often modulated by protein-protein interactions (PPIs) and therefore defining the partners of a protein helps to understand its activity. PPIs can be detected through different experimental approaches and are collected in several expert curated databases. These databases are used...
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| Veröffentlicht in: | PloS one 2012-02, Vol.7 (2), p.e31826-e31826 |
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| creator | Schaefer, Martin H Fontaine, Jean-Fred Vinayagam, Arunachalam Porras, Pablo Wanker, Erich E Andrade-Navarro, Miguel A |
| description | Protein function is often modulated by protein-protein interactions (PPIs) and therefore defining the partners of a protein helps to understand its activity. PPIs can be detected through different experimental approaches and are collected in several expert curated databases. These databases are used by researchers interested in examining detailed information on particular proteins. In many analyses the reliability of the characterization of the interactions becomes important and it might be necessary to select sets of PPIs of different confidence levels. To this goal, we generated HIPPIE (Human Integrated Protein-Protein Interaction rEference), a human PPI dataset with a normalized scoring scheme that integrates multiple experimental PPI datasets. HIPPIE's scoring scheme has been optimized by human experts and a computer algorithm to reflect the amount and quality of evidence for a given PPI and we show that these scores correlate to the quality of the experimental characterization. The HIPPIE web tool (available at http://cbdm.mdc-berlin.de/tools/hippie) allows researchers to do network analyses focused on likely true PPI sets by generating subnetworks around proteins of interest at a specified confidence level. |
| doi_str_mv | 10.1371/journal.pone.0031826 |
| format | Article |
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PPIs can be detected through different experimental approaches and are collected in several expert curated databases. These databases are used by researchers interested in examining detailed information on particular proteins. In many analyses the reliability of the characterization of the interactions becomes important and it might be necessary to select sets of PPIs of different confidence levels. To this goal, we generated HIPPIE (Human Integrated Protein-Protein Interaction rEference), a human PPI dataset with a normalized scoring scheme that integrates multiple experimental PPI datasets. HIPPIE's scoring scheme has been optimized by human experts and a computer algorithm to reflect the amount and quality of evidence for a given PPI and we show that these scores correlate to the quality of the experimental characterization. The HIPPIE web tool (available at http://cbdm.mdc-berlin.de/tools/hippie) allows researchers to do network analyses focused on likely true PPI sets by generating subnetworks around proteins of interest at a specified confidence level.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0031826</identifier><identifier>PMID: 22348130</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Acids ; Algorithms ; Autophagy ; Biology ; Computational Biology ; Computer Science ; Confidence intervals ; Controlled vocabularies ; Correlation analysis ; Data bases ; Databases, Protein ; Datasets ; Genomes ; Humans ; Internet ; Kinases ; Medical research ; Medicine ; Online data bases ; Protein interaction ; Protein Interaction Mapping - methods ; Protein-protein interactions ; Proteins ; Release dates ; Reliability analysis ; Research methodology ; Scoring ; Software ; Studies ; Web site management software</subject><ispartof>PloS one, 2012-02, Vol.7 (2), p.e31826-e31826</ispartof><rights>COPYRIGHT 2012 Public Library of Science</rights><rights>2012 Schaefer et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Schaefer et al. 2012</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c691t-a793dfa267d138b76e160ba6b62eb757ea5d3589248274db2ad265590536a1e73</citedby><cites>FETCH-LOGICAL-c691t-a793dfa267d138b76e160ba6b62eb757ea5d3589248274db2ad265590536a1e73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3279424/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3279424/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/22348130$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Deane, Charlotte M.</contributor><creatorcontrib>Schaefer, Martin H</creatorcontrib><creatorcontrib>Fontaine, Jean-Fred</creatorcontrib><creatorcontrib>Vinayagam, Arunachalam</creatorcontrib><creatorcontrib>Porras, Pablo</creatorcontrib><creatorcontrib>Wanker, Erich E</creatorcontrib><creatorcontrib>Andrade-Navarro, Miguel A</creatorcontrib><title>HIPPIE: Integrating protein interaction networks with experiment based quality scores</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Protein function is often modulated by protein-protein interactions (PPIs) and therefore defining the partners of a protein helps to understand its activity. 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One</addtitle><date>2012-02-14</date><risdate>2012</risdate><volume>7</volume><issue>2</issue><spage>e31826</spage><epage>e31826</epage><pages>e31826-e31826</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Protein function is often modulated by protein-protein interactions (PPIs) and therefore defining the partners of a protein helps to understand its activity. PPIs can be detected through different experimental approaches and are collected in several expert curated databases. These databases are used by researchers interested in examining detailed information on particular proteins. In many analyses the reliability of the characterization of the interactions becomes important and it might be necessary to select sets of PPIs of different confidence levels. To this goal, we generated HIPPIE (Human Integrated Protein-Protein Interaction rEference), a human PPI dataset with a normalized scoring scheme that integrates multiple experimental PPI datasets. HIPPIE's scoring scheme has been optimized by human experts and a computer algorithm to reflect the amount and quality of evidence for a given PPI and we show that these scores correlate to the quality of the experimental characterization. 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| subjects | Acids Algorithms Autophagy Biology Computational Biology Computer Science Confidence intervals Controlled vocabularies Correlation analysis Data bases Databases, Protein Datasets Genomes Humans Internet Kinases Medical research Medicine Online data bases Protein interaction Protein Interaction Mapping - methods Protein-protein interactions Proteins Release dates Reliability analysis Research methodology Scoring Software Studies Web site management software |
| title | HIPPIE: Integrating protein interaction networks with experiment based quality scores |
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