GPCR–drug interactions prediction using random forest with drug-association-matrix-based post-processing procedure-Reference-Cited by-同舟云学术

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GPCR–drug interactions prediction using random forest with drug-association-matrix-based post-processing procedure

Published:2016-02 Issue: Volume:60 Page:59-71
ISSN:1476-9271
Container-title:Computational Biology and Chemistry
language:en
Short-container-title:Computational Biology and Chemistry

Author:

Hu Jun,Li Yang,Yang Jing-Yu,Shen Hong-Bin,Yu Dong-Jun^ORCID

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

“The Six Top Talents” of Jiangsu Province

Graduate Research and Innovation Project of Jiangsu Province

Natural Science Foundation of Jiangsu

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Computational Mathematics,Organic Chemistry,Biochemistry,Structural Biology

Reference68 articles.

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2. Over-optimism in bioinformatics research;Boulesteix;Bioinformatics,2010

3. Random forests;Breiman;Mach. Learn.,2001

4. Prediction of transporter targets using efficient RBF networks with PSSM profiles and biochemical properties;Chen;Bioinformatics,2011

5. Structure-based maximal affinity model predicts small-molecule druggability;Cheng;Nat. Biotechnol.,2007

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