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...

Full description

Bibliographic Details
Main Author: Gregorio eAlanis-Lobato
Format: Article
Language:English
Published: Frontiers Media S.A. 2015-09-01
Series:Frontiers in Genetics
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fgene.2015.00296/full
id doaj-9ea6d8475b21443489623f46a0c02a20
record_format Article
spelling 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
work_keys_str_mv AT gregorioealanislobato miningproteininteractomestoimprovetheirreliabilityandsupporttheadvancementofnetworkmedicine
AT gregorioealanislobato miningproteininteractomestoimprovetheirreliabilityandsupporttheadvancementofnetworkmedicine
_version_ 1725385096204124160