| Graph convolutional networks for computational drug development and discovery M Sun, S Zhao, C Gilvary, O Elemento, J Zhou, F Wang Briefings in bioinformatics 21 (3), 919-935, 2020 | 365 | 2020 |
| Artificial intelligence in cancer research and precision medicine B Bhinder, C Gilvary, NS Madhukar, O Elemento Cancer discovery 11 (4), 900-915, 2021 | 346 | 2021 |
| The missing pieces of artificial intelligence in medicine C Gilvary, N Madhukar, J Elkhader, O Elemento Trends in pharmacological sciences 40 (8), 555-564, 2019 | 78 | 2019 |
| Dopamine receptor D5 is a modulator of tumor response to dopamine receptor D2 antagonism VV Prabhu, NS Madhukar, C Gilvary, CLB Kline, S Oster, WS El-Deiry, ... Clinical Cancer Research 25 (7), 2305-2313, 2019 | 59 | 2019 |
| Artificial Intelligence in Cancer Research and Precision Medicine. Cancer Discov. 2021 Apr; 11 (4): 900-915. doi: 10.1158/2159-8290 B Bhinder, C Gilvary, NS Madhukar, O Elemento CD-21-0090, 0 | 35 | |
| Multi-task learning predicts drug combination synergy in cells and in the clinic C Gilvary, JR Dry, O Elemento BioRxiv, 576017, 2019 | 19 | 2019 |
| A machine learning and network framework to discover new indications for small molecules C Gilvary, J Elkhader, N Madhukar, C Henchcliffe, MD Goncalves, ... PLoS computational biology 16 (8), e1008098, 2020 | 17 | 2020 |
| Artificial intelligence in cancer research and precision medicine. Cancer Discov 11: 900–915 B Bhinder, C Gilvary, NS Madhukar, O Elemento | 12 | 2021 |
| Artificial Intelligence in Cancer Research and Precision Medicine. Cancer discovery; 11 (4): 900–915 B Bhinder, C Gilvary, N Madhukar, O Elemento | 10 | 2021 |
| A machine learning approach predicts essential genes and pharmacological targets in cancer C Gilvary, NS Madhukar, K Gayvert, M Foronda, A Perez, CS Leslie, ... BioRxiv, 692277, 2019 | 5 | 2019 |
| A machine learning approach predicts tissue-specific drug adverse events NS Madhukar, K Gayvert, C Gilvary, O Elemento bioRxiv, 288332, 2018 | 5 | 2018 |
| A machine learning approach to identifying novel therapeutics and their underlying mechanisms CM Gilvary Weill Medical College of Cornell University, 2019 | 1 | 2019 |
| A data driven approach to predicting tissue-specific adverse events KM Gayvert, N Madhukar, C Gilvary, O Elemento Cancer Research 77 (13_Supplement), 5039-5039, 2017 | 1 | 2017 |
| A machine learning approach to predict platform specific gene essentiality in cancer CM Gilvary, NS Madhukar, KM Gayvert, DS Rickman, O Elemento Cancer Research 77 (13_Supplement), 1563-1563, 2017 | 1 | 2017 |
| Identification of synthetic lethal gene interactions to discover novel cancer vulnerabilities and guide drug development M Parikh, M Garcia-Quismondo, NS Madhukar, C Gilvary Cancer Research 82 (12_Supplement), 5062-5062, 2022 | | 2022 |
| Predicting target driven toxicity for small molecule inhibitors to aid in drug development M Garcia-Quismondo, M Parikh, N Madhukar, C Gilvary Cancer Research 82 (12_Supplement), 5063-5063, 2022 | | 2022 |
| Identifying novel oncology targets and positioning existing targets through the prediction of cancer dependencies. M Parikh, O Elemento, N Madhukar, C Gilvary CANCER RESEARCH 81 (13), 2021 | | 2021 |
| Prediction of genomic based drug sensitivity signatures to enable optimal drug positioning C Gilvary, O Elemento, N Madhukar Cancer Research 81 (13_Supplement), 395-395, 2021 | | 2021 |
| Identifying genetic interactions resulting form diverse biological mechanisms to inform cancer drug development M Garcia-Quismondo, O Elemento, N Madhukar, C Gilvary Cancer Research 81 (13_Supplement), 219-219, 2021 | | 2021 |
| Abstract B031: OneThree Biotech’s artificial intelligence platform for optimizing drug development C Gilvary, N Madhukar, O Elemento Molecular Cancer Therapeutics 18 (12_Supplement), B031-B031, 2019 | | 2019 |
