Minjun Chen
Minjun Chen
the US FDA's National Center for Toxicological Research
Verified email at - Homepage
Cited by
Cited by
The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.
L Shi, G Campbell, WD Jones, F Campagne, Z Wen, SJ Walker, Z Su, ...
Nature biotechnology 28 (8), 827, 2010
Drug-induced liver injury: Interactions between drug properties and host factors
M Chen, A Suzuki, J Borlak, RJ Andrade, MI Lucena
Journal of hepatology 63 (2), 503-514, 2015
FDA-approved drug labeling for the study of drug-induced liver injury
M Chen, V Vijay, Q Shi, Z Liu, H Fang, W Tong
Drug discovery today 16 (15-16), 697-703, 2011
High lipophilicity and high daily dose of oral medications are associated with significant risk for drug‐induced liver injury
M Chen, J Borlak, W Tong
Hepatology 58 (1), 388-396, 2013
DILIrank: the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans
M Chen, A Suzuki, S Thakkar, K Yu, C Hu, W Tong
Drug discovery today 21 (4), 648-653, 2016
Application of ethyl chloroformate derivatization for gas chromatography-mass spectrometry based metabonomic profiling
Y Qiu, M Su, Y Liu, M Chen, J Gu, J Zhang, W Jia
Analytica chimica acta 583 (2), 277-283, 2007
Metabonomic study on the biochemical profiles of a hydrocortisone-induced animal model
M Chen, L Zhao, W Jia
Journal of proteome research 4 (6), 2391-2396, 2005
Metabonomic study of aristolochic acid-induced nephrotoxicity in rats
M Chen, M Su, L Zhao, J Jiang, P Liu, J Cheng, Y Lai, Y Liu, W Jia
Journal of proteome research 5 (4), 995-1002, 2006
A Decade of Toxicogenomic Research and Its Contribution to Toxicological Science
M Chen, M Zhang, J Borlak, W Tong
Toxicological Sciences, 2012
Metabolic profiling using combined GC-MS and LC-MS provides a systems understanding of aristolochic acid-induced nephrotoxicity in rat
Y Ni, M Su, Y Qiu, M Chen, Y Liu, A Zhao, W Jia
FEBS letters 581 (4), 707-711, 2007
Measures for determining the similarity of chemical fingerprint and a method of evaluating the measures
YY Cheng, MJ Chen, YJ Wu
[Application of metabonomics in complicated theory system research of traditional Chinese medicine]
W Jia, P Liu, J Jiang, MJ Chen, LP Zhao, MM Zhou, LP Yang, MQ Wang, ...
Zhongguo Zhong yao za zhi= Zhongguo zhongyao zazhi= China journal of Chinese …, 2006
Predicting Hepatotoxicity Using ToxCast in Vitro Bioactivity and Chemical Structure
J Liu, K Mansouri, RS Judson, MT Martin, H Hong, M Chen, X Xu, ...
Chemical research in toxicology 28 (4), 738-751, 2015
Toward predictive models for drug-induced liver injury in humans: are we there yet?
M Chen, H Bisgin, L Tong, H Hong, H Fang, J Borlak, W Tong
Biomarkers in medicine 8 (2), 201-213, 2014
High daily dose and being a substrate of cytochrome P450 enzymes are two important predictors of drug-induced liver injury
K Yu, X Geng, M Chen, J Zhang, B Wang, K Ilic, W Tong
Drug Metabolism and Disposition 42 (4), 744-750, 2014
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
M Chen, H Hong, H Fang, R Kelly, G Zhou, J Borlak, W Tong
toxicological sciences 136 (1), 242-249, 2013
A review on machine learning methods for in silico toxicity prediction
G Idakwo, J Luttrell, M Chen, H Hong, Z Zhou, P Gong, C Zhang
Journal of Environmental Science and Health, Part C 36 (4), 169-191, 2018
The liver toxicity knowledge base: a systems approach to a complex end point
M Chen, J Zhang, Y Wang, Z Liu, R Kelly, G Zhou, H Fang, J Borlak, ...
Clinical Pharmacology & Therapeutics 93 (5), 409-412, 2013
A Model to predict severity of drug‐induced liver injury in humans
M Chen, J Borlak, W Tong
Hepatology 64 (3), 931-940, 2016
Development of decision forest models for prediction of drug-induced liver injury in humans using a large set of FDA-approved drugs
H Hong, S Thakkar, M Chen, W Tong
Scientific reports 7 (1), 17311, 2017
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