Deep Learning for Drug-Induced Liver Injury-Reference-Cited by-同舟云学术

Deep Learning for Drug-Induced Liver Injury

Published:2015-10-13 Issue:10 Volume:55 Page:2085-2093
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Xu Youjun¹,Dai Ziwei¹,Chen Fangjin¹,Gao Shuaishi¹,Pei Jianfeng¹,Lai Luhua¹²³

Affiliation:

1. Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China

2. Beijing National Laboratory for Molecular Sciences, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China

3. Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China

Funder

Ministry of Science and Technology of the People's Republic of China

National Natural Science Foundation of China

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/acs.jcim.5b00238

Reference65 articles.

1. Guidance for Industry Drug-Induced Liver Injury: Premarketing Clinical Evaluation;Food and Drug Administration:Silver Spring, MD, 2009; pp38035–38036.

2. LiverTox: A website on drug-induced liver injury

3. Human drug hepatotoxicity: a contemporary clinical perspective

4. Quantitative Structure-Activity Relationship Models for Predicting Drug-Induced Liver Injury Based on FDA-Approved Drug Labeling Annotation and Using a Large Collection of Drugs

5. Computational chemistry approach for the early detection of drug-induced idiosyncratic liver toxicity

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