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 | 204 | 2019 |
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 | 190 | 2020 |
CATMoS: collaborative acute toxicity modeling suite K Mansouri, AL Karmaus, J Fitzpatrick, G Patlewicz, P Pradeep, D Alberga, ... Environmental health perspectives 129 (4), 047013, 2021 | 117 | 2021 |
Revealing adverse outcome pathways from public high-throughput screening data to evaluate new toxicants by a knowledge-based deep neural network approach HL Ciallella, DP Russo, LM Aleksunes, FA Grimm, H Zhu Environmental science & technology 55 (15), 10875-10887, 2021 | 43 | 2021 |
Predictive modeling of estrogen receptor agonism, antagonism, and binding activities using machine-and deep-learning approaches HL Ciallella, DP Russo, LM Aleksunes, FA Grimm, H Zhu Laboratory investigation 101 (4), 490-502, 2021 | 41 | 2021 |
Construction of a virtual opioid bioprofile: a data-driven QSAR modeling study to identify new analgesic opioids X Jia, HL Ciallella, DP Russo, L Zhao, MH James, H Zhu ACS sustainable chemistry & engineering 9 (10), 3909-3919, 2021 | 27 | 2021 |
Predicting prenatal developmental toxicity based on the combination of chemical structures and biological data HL Ciallella, DP Russo, S Sharma, Y Li, E Sloter, L Sweet, H Huang, ... Environmental science & technology 56 (9), 5984-5998, 2022 | 26 | 2022 |
Extended stability evaluation of selected cathinones HL Ciallella, LR Rutter, LA Nisbet, KS Scott Frontiers in chemistry 8, 597726, 2020 | 25 | 2020 |
Data-driven quantitative structure–activity relationship modeling for human carcinogenicity by chronic oral exposure E Chung, DP Russo, HL Ciallella, YT Wang, M Wu, LM Aleksunes, H Zhu Environmental Science & Technology 57 (16), 6573-6588, 2023 | 21 | 2023 |
Hybrid non-animal modeling: A mechanistic approach to predict chemical hepatotoxicity E Chung, X Wen, X Jia, HL Ciallella, LM Aleksunes, H Zhu Journal of Hazardous Materials 471, 134297, 2024 | 4 | 2024 |
Automatic quantitative structure–activity relationship modeling to fill data gaps in high-throughput screening HL Ciallella, E Chung, DP Russo, H Zhu High-Throughput Screening Assays in Toxicology, 169-187, 2022 | 4 | 2022 |
High-throughput screening assays in toxicology MS Attene-Ramos, E Chung, HL Ciallella, S Dasgupta, WX Ding, ... Springer US, 2022 | 1 | 2022 |
A computationally supported designer benzodiazepine strategy for public toxicology laboratories HL Ciallella, DT Taruvinga, K Yacoub, S Sofalvi, SM Delor, CK Kaspar, ... Journal of Analytical Toxicology 48 (8), 541-549, 2024 | | 2024 |
Predicting Developmental and Reproductive Toxicity Using Artificial Intelligence and High-Throughput Screening Data HL Ciallella Rutgers, The State University of New Jersey-Camden, 2022 | | 2022 |
Erratum: CATMoS: Collaborative Acute Toxicity Modeling Suite A Sayed, AH Polash, JB Brown, X Li, N Alépée, O Nicolotti, A Varnek, ... Environmental Health Perspectives 129, 2021 | | 2021 |
Stability of AH-7921 in polar organic solvents M Murphy, H Ciallella, K Scott ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY 253, 2017 | | 2017 |
Stability of selected cathinones in methanol and acetonitrile H Ciallella, K Scott ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY 252, 2016 | | 2016 |