| 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 | 709 | 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 | 443 | 2008 |
| Big data and artificial intelligence modeling for drug discovery H Zhu Annual review of pharmacology and toxicology 60, 573-589, 2020 | 357 | 2020 |
| 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 | 334 | 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 | 305 | 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 | 273 | 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 | 228 | 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, 1902-1914, 2008 | 220 | 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 | 202 | 2001 |
| 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 | 196 | 2016 |
| Advancing Computational Toxicology in the Big Data Era by Artificial Intelligence: Data-Driven and Mechanism-Driven Modeling for Chemical Toxicity HL Ciallella, H Zhu Chemical research in toxicology 32 (4), 536-547, 2019 | 164 | 2019 |
| 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 | 151 | 2014 |
| Advancing computer-aided drug discovery (CADD) by big data and data-driven machine learning modeling L Zhao, HL Ciallella, LM Aleksunes, H Zhu Drug discovery today 25 (9), 1624-1638, 2020 | 150 | 2020 |
| 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 | 146 | 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 | 127 | 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 | 126 | 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 | 118 | 2014 |
| 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 | 110 | 2016 |
| Critical evaluation of human oral bioavailability for pharmaceutical drugs by using various cheminformatics approaches MT Kim, A Sedykh, SK Chakravarti, RD Saiakhov, H Zhu Pharmaceutical research 31, 1002-1014, 2014 | 108 | 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 | 107 | 2013 |
Alexander SedykhSenior Cheminformatics Scientist, Sciome LLC, NC在 sciome.com 的电子邮件经过验证
