| Informatics and computational methods in natural product drug discovery: a review and perspectives JD Romano, NP Tatonetti Frontiers in genetics 10, 368, 2019 | 194 | 2019 |
| PMLB v1. 0: an open-source dataset collection for benchmarking machine learning methods JD Romano, TT Le, W La Cava, JT Gregg, DJ Goldberg, P Chakraborty, ... Bioinformatics 38 (3), 878-880, 2022 | 159 | 2022 |
| Systems biology approaches for identifying adverse drug reactions and elucidating their underlying biological mechanisms MR Boland, A Jacunski, T Lorberbaum, JD Romano, R Moskovitch, ... Wiley Interdisciplinary Reviews: Systems Biology and Medicine 8 (2), 104-122, 2016 | 54 | 2016 |
| TPOT-NN: augmenting tree-based automated machine learning with neural network estimators JD Romano, TT Le, W Fu, JH Moore Genetic Programming and Evolvable Machines 22 (2), 207-227, 2021 | 46* | 2021 |
| The Alzheimer’s Knowledge Base: A Knowledge Graph for Alzheimer Disease Research JD Romano, V Truong, R Kumar, M Venkatesan, BE Graham, Y Hao, ... Journal of Medical Internet Research 26, e46777, 2024 | 38 | 2024 |
| Knowledge-guided deep learning models of drug toxicity improve interpretation Y Hao, JD Romano, JH Moore Patterns 3 (9), 100565, 2022 | 37 | 2022 |
| The promise of automated machine learning for the genetic analysis of complex traits E Manduchi, JD Romano, JH Moore Human Genetics 141 (9), 1529-1544, 2022 | 33 | 2022 |
| Automating Predictive Toxicology Using ComptoxAI JD Romano, Y Hao, JH Moore, TM Penning Chemical Research in Toxicology 35 (8), 1370-1382, 2022 | 27 | 2022 |
| Embedding covariate adjustments in tree-based automated machine learning for biomedical big data analyses E Manduchi, W Fu, JD Romano, S Ruberto, JH Moore BMC bioinformatics 21 (1), 430, 2020 | 26 | 2020 |
| Centralized and Federated Models for the Analysis of Clinical Data R Li, JD Romano, Y Chen, JH Moore Annual Review of Biomedical Data Science 7, 2024 | 18 | 2024 |
| Improving QSAR modeling for predictive toxicology using publicly aggregated semantic graph data and graph neural networks JD Romano, Y Hao, JH Moore Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing 27, 187, 2022 | 18 | 2022 |
| VenomKB, a new knowledge base for facilitating the validation of putative venom therapies JD Romano, NP Tatonetti Scientific data 2 (1), 1-9, 2015 | 12 | 2015 |
| Ten simple rules for writing a paper about scientific software JD Romano, JH Moore PLOS Computational Biology 16 (11), e1008390, 2020 | 7 | 2020 |
| Knowledge graph aids comprehensive explanation of drug and chemical toxicity Y Hao, JD Romano, JH Moore CPT: Pharmacometrics & Systems Pharmacology 12 (8), 1072-1079, 2023 | 6 | 2023 |
| Exploring genetic influences on adverse outcome pathways using heuristic simulation and graph data science JD Romano, L Mei, J Senn, JH Moore, HM Mortensen Computational Toxicology 25, 100261, 2023 | 6 | 2023 |
| VenomKB v2. 0: A knowledge repository for computational toxinology J Romano, V Nwankwo, N Tatonetti bioRxiv, 295204, 2018 | 6 | 2018 |
| Adapting simultaneous analysis phylogenomic techniques to study complex disease gene relationships JD Romano, WG Tharp, IN Sarkar Journal of biomedical informatics 54, 10-38, 2015 | 6 | 2015 |
| CASTER-DTA: Equivariant Graph Neural Networks for Predicting Drug-Target Affinity R Kumar, JD Romano, MD Ritchie bioRxiv, 2024.11. 25.625281, 2024 | 5 | 2024 |
| Discovering Venom-Derived Drug Candidates Using Differential Gene Expression JD Romano, H Li, T Napolitano, R Realubit, C Karan, M Holford, ... Toxins 15 (7), 451, 2023 | 5 | 2023 |
| Network-based analyses of multiomics data in biomedicine R Kumar, JD Romano, MD Ritchie BioData Mining 18 (1), 1-22, 2025 | 4 | 2025 |
Jason H. MooreChair, Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CAVerified email at csmc.edu
