Exploiting machine learning for end-to-end drug discovery and development S Ekins, AC Puhl, KM Zorn, TR Lane, DP Russo, JJ Klein, AJ Hickey, ... Nature materials 18 (5), 435-441, 2019 | 454 | 2019 |
Comparison of deep learning with multiple machine learning methods and metrics using diverse drug discovery data sets A Korotcov, V Tkachenko, DP Russo, S Ekins Molecular pharmaceutics 14 (12), 4462-4475, 2017 | 340 | 2017 |
T4 report: Toward good read-across practice (GRAP) guidance N Ball, MTD Cronin, J Shen, K Blackburn, ED Booth, M Bouhifd, E Donley, ... Altex 33 (2), 149, 2016 | 194 | 2016 |
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 | 144 | 2018 |
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 | 111 | 2016 |
Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug Discovery T Lane, DP Russo, KM Zorn, AM Clark, A Korotcov, V Tkachenko, ... Molecular pharmaceutics 15 (10), 4346-4360, 2018 | 94 | 2018 |
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 | 93 | 2021 |
Predicting nano–bio interactions by integrating nanoparticle libraries and quantitative nanostructure activity relationship modeling W Wang, A Sedykh, H Sun, L Zhao, DP Russo, H Zhou, B Yan, H Zhu ACS nano 11 (12), 12641-12649, 2017 | 90 | 2017 |
Nonanimal models for acute toxicity evaluations: applying data-driven profiling and read-across DP Russo, J Strickland, AL Karmaus, W Wang, S Shende, T Hartung, ... Environmental health perspectives 127 (4), 047001, 2019 | 73 | 2019 |
Global analysis of publicly available safety data for 9,801 substances registered under REACH from 2008–2014 T Luechtefeld, A Maertens, DP Russo, C Rovida, H Zhu, T Hartung Altex 33 (2), 95, 2016 | 70 | 2016 |
Analysis of publically available skin sensitization data from REACH registrations 2008–2014 T Luechtefeld, A Maertens, DP Russo, C Rovida, H Zhu, T Hartung Altex 33 (2), 135, 2016 | 64 | 2016 |
Abnormal functional relationship of sensorimotor network with neurotransmitter-related nuclei via subcortical-cortical loops in manic and depressive phases of bipolar disorder M Martino, P Magioncalda, B Conio, L Capobianco, D Russo, ... Schizophrenia Bulletin 46 (1), 163-174, 2020 | 63 | 2020 |
Multiple machine learning comparisons of HIV cell-based and reverse transcriptase data sets KM Zorn, TR Lane, DP Russo, AM Clark, V Makarov, S Ekins Molecular pharmaceutics 16 (4), 1620-1632, 2019 | 56 | 2019 |
Analysis of public oral toxicity data from REACH registrations 2008–2014 T Luechtefeld, A Maertens, DP Russo, C Rovida, H Zhu, T Hartung Altex 33 (2), 111, 2016 | 49 | 2016 |
Opposing changes in the functional architecture of large-scale networks in bipolar mania and depression D Russo, M Martino, P Magioncalda, M Inglese, M Amore, G Northoff Schizophrenia bulletin 46 (4), 971-980, 2020 | 47 | 2020 |
White matter microstructure alterations correlate with terminally differentiated CD8+ effector T cell depletion in the peripheral blood in mania: combined DTI and immunological … P Magioncalda, M Martino, S Tardito, B Sterlini, B Conio, V Marozzi, ... Brain, Behavior, and Immunity 73, 192-204, 2018 | 44 | 2018 |
Prediction of Nano–Bio Interactions through Convolutional Neural Network Analysis of Nanostructure Images X Yan, J Zhang, DP Russo, H Zhu, B Yan ACS Sustainable Chemistry & Engineering 8 (51), 19096-19104, 2020 | 36 | 2020 |
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 | 35 | 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 | 35 | 2021 |
CIIPro: a new read-across portal to fill data gaps using public large-scale chemical and biological data DP Russo, MT Kim, W Wang, D Pinolini, S Shende, J Strickland, ... Bioinformatics 33 (3), 464-466, 2017 | 33 | 2017 |