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Drug Discov Today. 2007 Apr;12(7-8):304-13. Epub 2007 Mar 7.

Support vector machines approach for predicting druggable proteins: recent progress in its exploration and investigation of its usefulness.

Author information

1
Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk Soc 1, Level 7, 3 Science Drive 2, Singapore 117543.

Abstract

Identification and validation of viable targets is an important first step in drug discovery and new methods, and integrated approaches are continuously explored to improve the discovery rate and exploration of new drug targets. An in silico machine learning method, support vector machines, has been explored as a new method for predicting druggable proteins from amino acid sequence independent of sequence similarity, thereby facilitating the prediction of druggable proteins that exhibit no or low homology to known targets.

PMID:
17395090
DOI:
10.1016/j.drudis.2007.02.015
[Indexed for MEDLINE]

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