title: QSAR based model for discriminating EGFR inhibitors and non-inhibitors using Random forest.
creator: Singh, Harinder
creator: Singh, Sandeep
creator: Singla, Deepak
creator: Agarwal, Subhash M
creator: Raghava, G.P.S.
subject: QR Microbiology
description: Epidermal Growth Factor Receptor (EGFR) is a well-characterized cancer drug target. In the past, several QSAR models have been developed for predicting inhibition activity of molecules against EGFR. These models are useful to a limited set of molecules for a particular class like quinazoline-derivatives. In this study, an attempt has been made to develop prediction models on a large set of molecules (~3500 molecules) that include diverse scaffolds like quinazoline, pyrimidine, quinoline and indole.
publisher: BioMedCentral
date: 2015
type: Article
type: PeerReviewed
format: application/pdf
identifier: http://crdd.osdd.net/open/1638/1/GPSR%202015%20prot%20str%20functio%20...24783.pdf
relation: http://www.biologydirect.com/content/10/1/10
identifier:   Singh, Harinder and Singh, Sandeep and Singla, Deepak and Agarwal, Subhash M and Raghava, G.P.S.  (2015) QSAR based model for discriminating EGFR inhibitors and non-inhibitors using Random forest.  Biology direct, 10.  p. 10.  ISSN 1745-6150     
relation: http://crdd.osdd.net/open/1638/