| Predicting the clinical impact of human mutation with deep neural networks L Sundaram, H Gao, SR Padigepati, JF McRae, Y Li, JA Kosmicki, ... Nature genetics 50 (8), 1161-1170, 2018 | 438 | 2018 |
| Deep learning-based techniques for pre-training deep convolutional neural networks H Gao, F Kai-How, SR PADIGEPATI US Patent 10,540,591, 2020 | 27 | 2020 |
| Deep convolutional neural networks for variant classification L Sundaram, F Kai-How, H Gao, SR PADIGEPATI, JF McRAE US Patent 11,315,016, 2022 | 22 | 2022 |
| Systems and Methods for the Interpretation of Genetic and Genomic Variants via an Integrated Computational and Experimental Deep Mutational Learning Framework CL Araya, JA Reuter, SR Padigepati, A Colavin US Patent App. 16/011,753, 2018 | 11 | 2018 |
| Interpretation of Genetic and Genomic Variants via an Integrated Computational and Experimental Deep Mutational Learning Framework CL Araya, JA Reuter, SR Padigepati, A Colavin US Patent App. 16/624,225, 2021 | 7 | 2021 |
| Scalable approaches for generating, validating and incorporating data from high-throughput functional assays to improve clinical variant classification SR Padigepati, DA Stafford, CA Tan, MR Silvis, K Jamieson, A Keyser, ... Human Genetics 143 (8), 995-1004, 2024 | 1 | 2024 |
| Systems and methods for the interpretation of genetic and genomic variants via an integrated computational and experimental deep mutational learning framework CL Araya, JA Reuter, SR Padigepati, A Colavin US Patent App. 18/081,459, 2023 | | 2023 |
| Variant pathogenicity prediction using neural network L Sundaram, F Kai-How, H Gao, SR PADIGEPATI, JF McRAE US Patent App. 17/715,001, 2022 | | 2022 |
