| Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen MP Menden, D Wang, MJ Mason, B Szalai, KC Bulusu, Y Guan, T Yu, ... Nature communications 10 (1), 1-17, 2019 | 325 | 2019 |
| Assessment of network module identification across complex diseases S Choobdar, ME Ahsen, J Crawford, M Tomasoni, T Fang, D Lamparter, ... Nature methods 16 (9), 843-852, 2019 | 294 | 2019 |
| Enhancing the interpretability of transcription factor binding site prediction using attention mechanism S Park, Y Koh, H Jeon, H Kim, Y Yeo, J Kang Scientific Reports 10 (1), 1-10, 2020 | 80 | 2020 |
| In silico drug combination discovery for personalized cancer therapy M Jeon, S Kim, S Park, H Lee, J Kang BMC systems biology 12 (2), 59-67, 2018 | 77 | 2018 |
| Crowdsourced mapping of unexplored target space of kinase inhibitors A Cichońska, B Ravikumar, RJ Allaway, F Wan, S Park, O Isayev, S Li, ... Nature communications 12 (1), 1-18, 2021 | 76 | 2021 |
| Deep learning of mutation-gene-drug relations from the literature K Lee, B Kim, Y Choi, S Kim, W Shin, S Lee, S Park, S Kim, AC Tan, ... BMC bioinformatics 19 (1), 1-13, 2018 | 52 | 2018 |
| A community challenge for a pancancer drug mechanism of action inference from perturbational profile data EF Douglass Jr, RJ Allaway, B Szalai, W Wang, T Tian, ... Cell Reports Medicine 3 (1), 100492, 2022 | 48 | 2022 |
| BRONCO: Biomedical entity Relation ONcology COrpus for extracting gene-variant-disease-drug relations K Lee, S Lee, S Park, S Kim, S Kim, K Choi, AC Tan, J Kang Database 2016, 2016 | 44 | 2016 |
| BTNET: boosted tree based gene regulatory network inference algorithm using time-course measurement data S Park, JM Kim, W Shin, SW Han, M Jeon, HJ Jang, IS Jang, J Kang BMC systems biology 12 (2), 69-77, 2018 | 42 | 2018 |
| Predicting mechanism of action of novel compounds using compound structure and transcriptomic signature coembedding G Jang, S Park, S Lee, S Kim, S Park, J Kang Bioinformatics 37 (Supplement_1), i376-i382, 2021 | 17 | 2021 |
| A deep learning model of tumor cell architecture elucidates response and resistance to CDK4/6 inhibitors S Park, E Silva, A Singhal, MR Kelly, K Licon, I Panagiotou, C Fogg, ... Nature Cancer, 1-14, 2024 | 16 | 2024 |
| Cancer mutations converge on a collection of protein assemblies to predict resistance to replication stress X Zhao, A Singhal, S Park, JH Kong, R Bachelder, T Ideker Cancer Discovery 14 (3), 508-523, 2024 | 13 | 2024 |
| Improving Tagging Consistency and Entity Coverage for Chemical Identification in Full-text Articles H Kim, M Sung, W Yoon, S Park, J Kang arXiv preprint arXiv:2111.10584, 2021 | 9 | 2021 |
| CONFIGURE: A pipeline for identifying context specific regulatory modules from gene expression data and its application to breast cancer S Park, D Hwang, YS Yeo, H Kim, J Kang BMC medical genomics 12 (5), 1-8, 2019 | 5 | 2019 |
| Prediction of immunotherapy response using mutations to cancer protein assemblies JH Kong, X Zhao, A Singhal, S Park, R Bachelder, J Shen, H Zhang, ... Science Advances 10 (38), eado9746, 2024 | 2 | 2024 |
| Predicting clinical drug responses using a few-shot learning-based interpretable AI S Park, A Singhal, E Silva, JF Kreisberg, T Ideker Cancer Research 82 (12_Supplement), 1159-1159, 2022 | 1 | 2022 |
| Cancer mutations converge on a constellation of molecular assemblies to predict resistance to replication stress agents X Zhao, A Singhal, SJ Park, JH Kong, R Bachelder, T Ideker Cancer Research 84 (6_Supplement), 4918-4918, 2024 | | 2024 |
| G2PT: Mechanistic genotype-phenotype translation using hierarchical transformers I Lee, S Park, H Nam, T Ideker Cancer Research 84 (6_Supplement), 7383-7383, 2024 | | 2024 |
| Mechanistic genotype-phenotype translation using hierarchical transformers I Lee, Z Wallace, S Park, H Nam, A Majithia, T Ideker bioRxiv, 2024.10. 23.619940, 2024 | | 2024 |
| Full-text chemical identification with improved generalizability and tagging consistency H Kim, M Sung, W Yoon, S Park, J Kang Database 2022, 2022 | | 2022 |