Evaluation of Virtual Screening Performance of Support Vector Machines Trained by Sparsely Distributed Active Compounds-Reference-Cited by-同舟云学术

Evaluation of Virtual Screening Performance of Support Vector Machines Trained by Sparsely Distributed Active Compounds

Published:2008-06-01 Issue:6 Volume:48 Page:1227-1237
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Ma X. H.¹,Wang R.¹,Yang S. Y.¹,Li Z. R.¹,Xue Y.¹,Wei Y. C.¹,Low B. C.¹,Chen Y. Z.¹

Affiliation:

1. Bioinformatics and Drug Design Group, Centre for Computational Science and Engineering, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543, State Key Laboratory of Biotherapy, Sichuan University, Chengdu 610064, P. R. China, College of Chemistry, Sichuan University, Chengdu, 610064, P. R. China, and Department of Biological Science, National University of Singapore, Blk S2, Level 5, Science Drive 4, Singapore 117543

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/ci800022e

Reference84 articles.

1. Virtual screening of chemical libraries

2. Novel technologies for virtual screening

3. Streamlining lead discovery by aligning in silico and high-throughput screening

5. Han, L. Y.; Ma, X. H.et al. A support vector machines approach for virtual screening of active compounds of single and multiple mechanisms from large libraries at an improved hit-rate and enrichment factorJ. Mol. Graphics Modell. 2007, accepted for publication.

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