| Structural genomics of SARS-CoV-2 indicates evolutionary conserved functional regions of viral proteins S Srinivasan, H Cui, Z Gao, M Liu, S Lu, W Mkandawire, O Narykov, ... Viruses 12 (4), 360, 2020 | 286* | 2020 |
| 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 | 262* | 2019 |
| Molecular architecture and dynamics of SARS-CoV-2 envelope by integrative modeling W Pezeshkian, F Grünewald, O Narykov, S Lu, V Arkhipova, ... Structure 31 (4), 492-503. e7, 2023 | 33 | 2023 |
| Deep learning methods for drug response prediction in cancer: predominant and emerging trends A Partin, TS Brettin, Y Zhu, O Narykov, A Clyde, J Overbeek, RL Stevens Frontiers in medicine 10, 1086097, 2023 | 25 | 2023 |
| DISPOT: a simple knowledge-based protein domain interaction statistical potential O Narykov, D Bogatov, D Korkin Bioinformatics 35 (24), 5374-5378, 2019 | 10 | 2019 |
| Predicting Protein Interaction Network Perturbation by Alternative Splicing with Semi-Supervised Learning O Narykov, NT Johnson, D Korkin Cell Reports 37 (Issue 8), 110045, 2021 | 9* | 2021 |
| Computational protein modeling and the next viral pandemic O Narykov, S Srinivasan, D Korkin Nature methods 18 (5), 444-445, 2021 | 9 | 2021 |
| Single-cell long-read sequencing-based mapping reveals specialized splicing patterns in developing and adult mouse and human brain A Joglekar, W Hu, B Zhang, O Narykov, M Diekhans, J Marrocco, ... Nature Neuroscience, 1-13, 2024 | 6* | 2024 |
| Integration of Computational Docking into Anti-Cancer Drug Response Prediction Models O Narykov, Y Zhu, T Brettin, YA Evrard, A Partin, M Shukla, F Xia, A Clyde, ... Cancers 16 (1), 50, 2023 | 2 | 2023 |
| A Comprehensive Investigation of Active Learning Strategies for Conducting Anti-Cancer Drug Screening P Vasanthakumari, Y Zhu, T Brettin, A Partin, M Shukla, F Xia, O Narykov, ... Cancers 16 (3), 530, 2024 | 1 | 2024 |
| Modern Computer Science Approaches in Biology: From Predicting Molecular Functions to Modeling Protein Structure O Narykov Worcester Polytechnic Institute, 2022 | 1 | 2022 |
| Structural Genomics and Interactomics of SARS-COV2: Decoding Basic Building Blocks of the Coronavirus Z Gao, S Lu, O Narykov, S Srinivasan, D Korkin Virus Bioinformatics, 121-139, 2021 | 1 | 2021 |
| Data Imbalance in Drug Response Prediction-Multi-Objective Optimization Approach in Deep Learning Setting O Narykov, Y Zhu, T Brettin, YA Evrard, A Partin, F Xia, M Shukla, ... bioRxiv, 2024.03. 14.585074, 2024 | | 2024 |
| Entropy-Based Regularization on Deep Learning Models for Anti-Cancer Drug Response Prediction O Narykov, Y Zhu, T Brettin, Y Evrard, A Partin, M Shukla, ... Proceedings of the SC'23 Workshops of The International Conference on High …, 2023 | | 2023 |
| Influencing factors on false positive rates when classifying tumor cell line response to drug treatment P Vasanthakumari, T Brettin, Y Zhu, H Yoo, M Shukla, A Partin, F Xia, ... arXiv preprint arXiv:2310.11329, 2023 | | 2023 |
| Systematic evaluation and comparison of drug response prediction models: a case study of prediction generalization across cell lines datasets A Partin, TS Brettin, Y Zhu, J Overbeek, O Narykov, P Vasanthakumari, ... Cancer Research 83 (7_Supplement), 5380-5380, 2023 | | 2023 |
| Molecular architecture of SARS-CoV-2 envelope by integrative modeling (preprint) W Pezeshkian, F Grunewald, O Narykov, S Lu, T Wassenaar, SJJ Marrink, ... | | 2021 |
Dmitry KorkinJurist Dean’s Professor of Computer Science, Worcester Polytechnic InstituteVerified email at korkinlab.org
