Predicting drug side effects by multi-label learning and ensemble learning-Reference-Cited by-同舟云学术

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Predicting drug side effects by multi-label learning and ensemble learning

Published:2015-11-04 Issue:1 Volume:16 Page:
ISSN:1471-2105
Container-title:BMC Bioinformatics
language:en
Short-container-title:BMC Bioinformatics

Author:

Zhang Wen,Liu Feng,Luo Longqiang,Zhang Jingxia

Funder

National Natural Science Foundation of China

Shenzhen development Foundation

China Scholarship Council

National Natural Science Foundation of China (CN)

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology

Link

http://link.springer.com/content/pdf/10.1186/s12859-015-0774-y.pdf

Reference33 articles.

1. Mizuno N, Niwa T, Yotsumoto Y, Sugiyama Y. Impact of drug transporter studies on drug discovery and development. Pharmacol Rev. 2003;55(3):425–61.

2. Fliri AF, Loging WT, Thadeio PF, Volkmann RA. Analysis of drug-induced effect patterns to link structure and side effects of medicines. Nat Chem Biol. 2005;1(7):389–97.

3. Merle L, Laroche ML, Dantoine T, Charmes JP. Predicting and preventing adverse drug reactions in the very old. Drugs Aging. 2005;22(5):375–92.

4. Bender A, Scheiber J, Glick M, Davies JW, Azzaoui K, Hamon J, et al. Analysis of pharmacology data and the prediction of adverse drug reactions and off-target effects from chemical structure. ChemMedChem. 2007;2(6):861–73.

5. Fukuzaki M, Seki M, Kashima H, Sese J. Side effect prediction using cooperative pathways. Bioinformatics and Biomedicine. 2009 BIBM'09 IEEE International Conference on: 2009. IEEE: Washington, DC. 142–147.

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