| Defining molecular initiating events in the adverse outcome pathway framework for risk assessment TEH Allen, JM Goodman, S Gutsell, PJ Russell Chemical Research in Toxicology 27 (12), 2100-2112, 2014 | 174 | 2014 |
| 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 | 105 | 2021 |
| Machine learning in predictive toxicology: recent applications and future directions for classification models MWH Wang, JM Goodman, TEH Allen Chemical research in toxicology 34 (2), 217-239, 2020 | 76 | 2020 |
| A History of the Molecular Initiating Event TEH Allen, JM Goodman, S Gutsell, PJ Russell Chemical Research in Toxicology 29 (11), 2060-2070, 2016 | 53 | 2016 |
| Vision of a near future: Bridging the human health–environment divide. Toward an integrated strategy to understand mechanisms across species for chemical safety assessment C Rivetti, TEH Allen, JB Brown, E Butler, PL Carmichael, JK Colbourne, ... Toxicology In Vitro 62, 104692, 2020 | 42 | 2020 |
| Machine learning informs RNA‐binding chemical space K Yazdani, D Jordan, M Yang, CR Fullenkamp, DR Calabrese, R Boer, ... Angewandte Chemie 135 (11), e202211358, 2023 | 37 | 2023 |
| Using 2D structural alerts to define chemical categories for molecular initiating events TEH Allen, JM Goodman, S Gutsell, PJ Russell Toxicological Sciences 165 (1), 213-223, 2018 | 34 | 2018 |
| Characterizing the coverage of critical effects relevant in the safety evaluation of food additives by AOPs NI Kramer, Y Hoffmans, S Wu, A Thiel, N Thatcher, TEH Allen, S Levorato, ... Archives of Toxicology 93, 2115-2125, 2019 | 32 | 2019 |
| Structural alerts and random forest models in a consensus approach for receptor binding molecular initiating events AJ Wedlake, M Folia, S Piechota, TEH Allen, JM Goodman, S Gutsell, ... Chemical Research in Toxicology 33 (2), 388-401, 2019 | 26 | 2019 |
| Neural network activation similarity: a new measure to assist decision making in chemical toxicology TEH Allen, AJ Wedlake, E Gelžinytė, C Gong, JM Goodman, S Gutsell, ... Chemical science 11 (28), 7335-7348, 2020 | 21 | 2020 |
| Using transition state modeling to predict mutagenicity for michael acceptors TEH Allen, MN Grayson, JM Goodman, S Gutsell, PJ Russell Journal of Chemical Information and Modeling 58 (6), 1266-1271, 2018 | 21 | 2018 |
| Using molecular initiating events to generate 2D structure–activity relationships for toxicity screening TEH Allen, S Liggi, JM Goodman, S Gutsell, PJ Russell Chemical Research in Toxicology 29 (10), 1611-1627, 2016 | 20 | 2016 |
| Quantitative predictions for molecular initiating events using three-dimensional Quantitative Structure–Activity Relationships TEH Allen, JM Goodman, S Gutsell, PJ Russell Chemical Research in Toxicology 33 (2), 324-332, 2019 | 19 | 2019 |
| Computers as Scientists TEH Allen Machine Learning in Chemistry, 1-15, 2020 | 18* | 2020 |
| Identification of a novel toxicophore in anti-cancer chemotherapeutics that targets mitochondrial respiratory complex I ZA Stephenson, RF Harvey, KR Pryde, S Mistry, RE Hardy, R Serreli, ... Elife 9, e55845, 2020 | 17 | 2020 |
| The use of adverse outcome pathways in the safety evaluation of food additives M Vinken, N Kramer, TEH Allen, Y Hoffmans, N Thatcher, S Levorato, ... Archives of Toxicology 94, 959-966, 2020 | 16 | 2020 |
| The role of ‘big data’and ‘in silico’New Approach Methodologies (NAMs) in ending animal use–A commentary on progress RN Ram, D Gadaleta, TEH Allen Computational Toxicology 23, 100232, 2022 | 14 | 2022 |
| In silico guidance for in vitro androgen and glucocorticoid receptor ToxCast assays TEH Allen, MD Nelms, SW Edwards, JM Goodman, S Gutsell, PJ Russell Environmental Science & Technology 54 (12), 7461-7470, 2020 | 8 | 2020 |
| Confidence in inactive and active predictions from structural alerts AJ Wedlake, TEH Allen, JM Goodman, S Gutsell, P Kukic, PJ Russell Chemical Research in Toxicology 33 (12), 3010-3022, 2020 | 4 | 2020 |
| Towards quantifying the uncertainty in in silico predictions using Bayesian learning TEH Allen, AM Middleton, JM Goodman, PJ Russell, P Kukic, S Gutsell Computational Toxicology 23, 100228, 2022 | 3 | 2022 |
