Mining protein interactomes to improve their reliability and support the advancement of network medicine

Handle URI:
http://hdl.handle.net/10754/581515
Title:
Mining protein interactomes to improve their reliability and support the advancement of network medicine
Authors:
Alanis Lobato, Gregorio ( 0000-0001-9339-4229 )
Abstract:
High-throughput detection of protein interactions has had a major impact in our understanding of the intricate molecular machinery underlying the living cell, and has permitted the construction of very large protein interactomes. The protein networks that are currently available are incomplete and a significant percentage of their interactions are false positives. Fortunately, the structural properties observed in good quality social or technological networks are also present in biological systems. This has encouraged the development of tools, to improve the reliability of protein networks and predict new interactions based merely on the topological characteristics of their components. Since diseases are rarely caused by the malfunction of a single protein, having a more complete and reliable interactome is crucial in order to identify groups of inter-related proteins involved in disease etiology. These system components can then be targeted with minimal collateral damage. In this article, an important number of network mining tools is reviewed, together with resources from which reliable protein interactomes can be constructed. In addition to the review, a few representative examples of how molecular and clinical data can be integrated to deepen our understanding of pathogenesis are discussed.
KAUST Department:
Integrative Systems Biology Lab; Biological and Environmental Sciences and Engineering (BESE) Division
Citation:
Mining protein interactomes to improve their reliability and support the advancement of network medicine 2015, 6 Frontiers in Genetics
Publisher:
Frontiers Media SA
Journal:
Frontiers in Genetics
Issue Date:
23-Sep-2015
DOI:
10.3389/fgene.2015.00296
Type:
Article
ISSN:
1664-8021
Additional Links:
http://journal.frontiersin.org/Article/10.3389/fgene.2015.00296/abstract
Appears in Collections:
Articles; Biological and Environmental Sciences and Engineering (BESE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorAlanis Lobato, Gregorioen
dc.date.accessioned2015-11-01T11:16:54Zen
dc.date.available2015-11-01T11:16:54Zen
dc.date.issued2015-09-23en
dc.identifier.citationMining protein interactomes to improve their reliability and support the advancement of network medicine 2015, 6 Frontiers in Geneticsen
dc.identifier.issn1664-8021en
dc.identifier.doi10.3389/fgene.2015.00296en
dc.identifier.urihttp://hdl.handle.net/10754/581515en
dc.description.abstractHigh-throughput detection of protein interactions has had a major impact in our understanding of the intricate molecular machinery underlying the living cell, and has permitted the construction of very large protein interactomes. The protein networks that are currently available are incomplete and a significant percentage of their interactions are false positives. Fortunately, the structural properties observed in good quality social or technological networks are also present in biological systems. This has encouraged the development of tools, to improve the reliability of protein networks and predict new interactions based merely on the topological characteristics of their components. Since diseases are rarely caused by the malfunction of a single protein, having a more complete and reliable interactome is crucial in order to identify groups of inter-related proteins involved in disease etiology. These system components can then be targeted with minimal collateral damage. In this article, an important number of network mining tools is reviewed, together with resources from which reliable protein interactomes can be constructed. In addition to the review, a few representative examples of how molecular and clinical data can be integrated to deepen our understanding of pathogenesis are discussed.en
dc.language.isoenen
dc.publisherFrontiers Media SAen
dc.relation.urlhttp://journal.frontiersin.org/Article/10.3389/fgene.2015.00296/abstracten
dc.rightsThis is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. http://creativecommons.org/licenses/by/4.0/en
dc.subjectinteractomeen
dc.subjectproteomeen
dc.subjectnetworken
dc.subjectreliabilityen
dc.subjectpredictionen
dc.subjectmedicineen
dc.subjectdiseaseen
dc.subjectpathogenesisen
dc.titleMining protein interactomes to improve their reliability and support the advancement of network medicineen
dc.typeArticleen
dc.contributor.departmentIntegrative Systems Biology Laben
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Divisionen
dc.identifier.journalFrontiers in Geneticsen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionFaculty of Biology, Institute of Molecular Biology, Johannes Gutenberg University of Mainz, Mainz, Germanyen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorAlanis Lobato, Gregorioen
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