In silico prediction of novel therapeutic targets using gene–disease association data

In silico prediction of novel therapeutic targets using gene–disease association data

Abstract Background Target identification and validation is a pressing challenge in the pharmaceutical industry, with many of the programmes that fail for efficacy reasons showing poor association between the drug target and the disease. Computational prediction of successful targets could have a co...

Full description

Bibliographic Details
Main Authors: Enrico Ferrero, Ian Dunham, Philippe Sanseau
Format: Article
Language:English
Published: BMC 2017-08-01
Series:Journal of Translational Medicine
Subjects:
Drug discovery
Target discovery
Gene–disease associations
Machine learning
Data mining
Online Access:http://link.springer.com/article/10.1186/s12967-017-1285-6

Similar Items

Similar Items