|From machine learning to deep learning: progress in machine intelligence for rational drug discovery|
L Zhang, J Tan, D Han, H Zhu
Drug discovery today 22 (11), 1680-1685, 2017
|Critical assessment of QSAR models of environmental toxicity against Tetrahymena pyriformis: focusing on applicability domain and overfitting by variable selection|
IV Tetko, I Sushko, AK Pandey, H Zhu, A Tropsha, E Papa, T Oberg, ...
Journal of chemical information and modeling 48 (9), 1733-1746, 2008
|Combinatorial QSAR modeling of chemical toxicants tested against Tetrahymena pyriformis|
H Zhu, A Tropsha, D Fourches, A Varnek, E Papa, P Gramatica, T Oberg, ...
Journal of chemical information and modeling 48 (4), 766-784, 2008
|Does rational selection of training and test sets improve the outcome of QSAR modeling?|
TM Martin, P Harten, DM Young, EN Muratov, A Golbraikh, H Zhu, ...
Journal of chemical information and modeling 52 (10), 2570-2578, 2012
|Quantitative structure− activity relationship modeling of rat acute toxicity by oral exposure|
H Zhu, TM Martin, L Ye, A Sedykh, DM Young, A Tropsha
Chemical research in toxicology 22 (12), 1913-1921, 2009
|Predicting drug-induced hepatotoxicity using QSAR and toxicogenomics approaches|
Y Low, T Uehara, Y Minowa, H Yamada, Y Ohno, T Urushidani, A Sedykh, ...
Chemical research in toxicology 24 (8), 1251-1262, 2011
|QSAR modeling of the blood–brain barrier permeability for diverse organic compounds|
L Zhang, H Zhu, TI Oprea, A Golbraikh, A Tropsha
Pharmaceutical research 25 (8), 1902-1914, 2008
|Estimation of the aqueous solubility of organic molecules by the group contribution approach|
G Klopman, H Zhu
Journal of chemical information and computer sciences 41 (2), 439-445, 2001
|Big data and artificial intelligence modeling for drug discovery|
Annual review of pharmacology and toxicology 60, 573, 2020
|Toward Good Read-Across Practice (GRAP) guidance.|
N Ball, MT Cronin, J Shen, MD Adenuga, K Blackburn, ED Booth, ...
ALTEX 33 (2), 149-166, 2016
|Big data in chemical toxicity research: the use of high-throughput screening assays to identify potential toxicants|
H Zhu, J Zhang, MT Kim, A Boison, A Sedykh, K Moran
Chemical research in toxicology 27 (10), 1643-1651, 2014
|Comparing Multiple Machine Learning Algorithms and Metrics for Estrogen Receptor Binding Prediction|
DP Russo, KM Zorn, AM Clark, H Zhu, S Ekins
Molecular pharmaceutics 15 (10), 4361-4370, 2018
|Use of in Vitro HTS-Derived Concentration–Response Data as Biological Descriptors Improves the Accuracy of QSAR Models of in Vivo Toxicity|
A Sedykh, H Zhu, H Tang, L Zhang, A Richard, I Rusyn, A Tropsha
Environmental health perspectives 119 (3), 364-370, 2011
|Modeling Liver-Related Adverse Effects of Drugs Using kNearest Neighbor Quantitative Structure−Activity Relationship Method|
AD Rodgers, H Zhu, D Fourches, I Rusyn, A Tropsha
Chemical research in toxicology 23 (4), 724-732, 2010
|Tuning cell autophagy by diversifying carbon nanotube surface chemistry|
L Wu, Y Zhang, C Zhang, X Cui, S Zhai, Y Liu, C Li, H Zhu, G Qu, G Jiang, ...
ACS nano 8 (3), 2087-2099, 2014
|Discovery of novel antimalarial compounds enabled by QSAR-based virtual screening|
L Zhang, D Fourches, A Sedykh, H Zhu, A Golbraikh, S Ekins, J Clark, ...
Journal of chemical information and modeling 53 (2), 475-492, 2013
|Recent methodologies for the estimation of n-octanol/water partition coefficients and their use in the prediction of membrane transport properties of drugs.|
G Klopman, H Zhu
Mini reviews in medicinal chemistry 5 (2), 127-133, 2005
|Use of cell viability assay data improves the prediction accuracy of conventional quantitative structure–activity relationship models of animal carcinogenicity|
H Zhu, I Rusyn, A Richard, A Tropsha
Environmental health perspectives 116 (4), 506-513, 2008
|Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR-and structure-based virtual screening approaches|
L Zhang, A Sedykh, A Tripathi, H Zhu, A Afantitis, VD Mouchlis, ...
Toxicology and applied pharmacology 272 (1), 67-76, 2013
|Analysis of Draize eye irritation testing and its prediction by mining publicly available 2008–2014 REACH data|
T Luechtefeld, A Maertens, DP Russo, C Rovida, H Zhu, T Hartung
Altex 33 (2), 123, 2016