Mining protein interactomes to improve their reliability and support the advancement of network medicine
Type
ArticleAuthors
Alanis Lobato, Gregorio
KAUST Department
Biological and Environmental Sciences and Engineering (BESE) DivisionComputer Science Program
Integrative Systems Biology Lab
Date
2015-09-23Permanent link to this record
http://hdl.handle.net/10754/581515
Metadata
Show full item recordAbstract
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.Citation
Mining protein interactomes to improve their reliability and support the advancement of network medicine 2015, 6 Frontiers in GeneticsPublisher
Frontiers Media SAJournal
Frontiers in GeneticsPubMed ID
26442112ae974a485f413a2113503eed53cd6c53
10.3389/fgene.2015.00296
Scopus Count
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