Mining protein interactomes to improve their reliability and support the advancement of network medicine
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...
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Online Access: | http://journal.frontiersin.org/Journal/10.3389/fgene.2015.00296/full |
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doaj-9ea6d8475b21443489623f46a0c02a202020-11-25T00:16:02ZengFrontiers Media S.A.Frontiers in Genetics1664-80212015-09-01610.3389/fgene.2015.00296153822Mining protein interactomes to improve their reliability and support the advancement of network medicineGregorio eAlanis-Lobato0Gregorio eAlanis-Lobato1Johannes Gutenberg UniversityKing Abdullah University of Science and TechonologyHigh-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 aetiology. 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.http://journal.frontiersin.org/Journal/10.3389/fgene.2015.00296/fullDiseaseHealthMedicineProteomenetworkPathogenesis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Gregorio eAlanis-Lobato Gregorio eAlanis-Lobato |
spellingShingle |
Gregorio eAlanis-Lobato Gregorio eAlanis-Lobato Mining protein interactomes to improve their reliability and support the advancement of network medicine Frontiers in Genetics Disease Health Medicine Proteome network Pathogenesis |
author_facet |
Gregorio eAlanis-Lobato Gregorio eAlanis-Lobato |
author_sort |
Gregorio eAlanis-Lobato |
title |
Mining protein interactomes to improve their reliability and support the advancement of network medicine |
title_short |
Mining protein interactomes to improve their reliability and support the advancement of network medicine |
title_full |
Mining protein interactomes to improve their reliability and support the advancement of network medicine |
title_fullStr |
Mining protein interactomes to improve their reliability and support the advancement of network medicine |
title_full_unstemmed |
Mining protein interactomes to improve their reliability and support the advancement of network medicine |
title_sort |
mining protein interactomes to improve their reliability and support the advancement of network medicine |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Genetics |
issn |
1664-8021 |
publishDate |
2015-09-01 |
description |
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 aetiology. 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. |
topic |
Disease Health Medicine Proteome network Pathogenesis |
url |
http://journal.frontiersin.org/Journal/10.3389/fgene.2015.00296/full |
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