ADMET evaluation in drug discovery: 15. Accurate prediction of rat oral acute toxicity using relevance vector machine and consensus modeling-Reference-Cited by-同舟云学术

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ADMET evaluation in drug discovery: 15. Accurate prediction of rat oral acute toxicity using relevance vector machine and consensus modeling

Published:2016-02-01 Issue:1 Volume:8 Page:
ISSN:1758-2946
Container-title:Journal of Cheminformatics
language:en
Short-container-title:J Cheminform

Author:

Lei Tailong,Li Youyong,Song Yunlong,Li Dan,Sun Huiyong,Hou Tingjun

Funder

National Science Foundation of China

National Natural Science Foundation of China

Special Program for National Basic Work on Science and Technology

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Computer Graphics and Computer-Aided Design,Physical and Theoretical Chemistry,Computer Science Applications

Link

http://link.springer.com/content/pdf/10.1186/s13321-016-0117-7.pdf

Reference80 articles.

1. Parasuraman S (2011) Toxicological screening. J Pharmacol Pharmacother 2(2):74

2. Nicolotti O, Benfenati E, Carotti A, Gadaleta D, Gissi A, Mangiatordi GF, Novellino E (2014) REACH and in silico methods: an attractive opportunity for medicinal chemists. Drug Discov Today 19(11):1757–1768

3. Benz RD (2007) Toxicological and clinical computational analysis and the US FDA/CDER. Expert Opin Drug Metab Toxicol 3(1):109–124

4. Creton S, Dewhurst IC, Earl LK, Gehen SC, Guest RL, Hotchkiss JA, Indans I, Woolhiser MR, Billington R (2009) Acute toxicity testing of chemicals—opportunities to avoid redundant testing and use alternative approaches. Crit Rev Toxicol 40(1):50–83

5. Cheng F, Li W, Liu G, Tang Y (2013) In silico ADMET prediction: recent advances, current challenges and future trends. Curr Top Med Chem 13(11):1273–1289

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