| Alphafold2-rave: From sequence to boltzmann ranking BP Vani, A Aranganathan, D Wang, P Tiwary Journal of chemical theory and computation 19 (14), 4351-4354, 2023 | 72 | 2023 |
| Long-time-scale predictions from short-trajectory data: A benchmark analysis of the trp-cage miniprotein J Strahan, A Antoszewski, C Lorpaiboon, BP Vani, J Weare, AR Dinner Journal of chemical theory and computation 17 (5), 2948-2963, 2021 | 40 | 2021 |
| Insulin dissociates by diverse mechanisms of coupled unfolding and unbinding A Antoszewski, CJ Feng, BP Vani, EH Thiede, L Hong, J Weare, ... The journal of physical chemistry B 124 (27), 5571-5587, 2020 | 39 | 2020 |
| Molecular dynamics simulations of nucleotide release from the circadian clock protein KaiC reveal atomic-resolution functional insights L Hong, BP Vani, EH Thiede, MJ Rust, AR Dinner Proceedings of the National Academy of Sciences 115 (49), E11475-E11484, 2018 | 34 | 2018 |
| Exploring kinase Asp-Phe-Gly (DFG) loop conformational stability with AlphaFold2-RAVE BP Vani, A Aranganathan, P Tiwary Journal of chemical information and modeling 64 (7), 2789-2797, 2023 | 24 | 2023 |
| Computing transition path theory quantities with trajectory stratification BP Vani, J Weare, AR Dinner The Journal of Chemical Physics 157 (3), 2022 | 19 | 2022 |
| Graph attention site prediction (GrASP): identifying druggable binding sites using graph neural networks with attention Z Smith, M Strobel, BP Vani, P Tiwary Journal of chemical information and modeling 64 (7), 2637-2644, 2024 | 17 | 2024 |
| From sequence to Boltzmann weighted ensemble of structures with AlphaFold2-RAVE BP Vani, A Aranganathan, D Wang, P Tiwary bioRxiv, 2022.05. 25.493365, 2022 | 5 | 2022 |
| Modeling Boltzmann weighted structural ensembles of proteins using AI based methods A Aranganathan, X Gu, D Wang, B Vani, P Tiwary | 4 | 2025 |
| Exploring kinase DFG loop conformational stability with AlphaFold2-RAVE BP Vani, A Aranganathan, P Tiwary ArXiv, arXiv: 2309.03649 v1, 2023 | 3 | 2023 |
| Modeling Boltzmann-weighted structural ensembles of proteins using artificial intelligence–based methods A Aranganathan, X Gu, D Wang, BP Vani, P Tiwary Current Opinion in Structural Biology 91, 103000, 2025 | 1 | 2025 |
| JAMUN: Transferable Molecular Conformational Ensemble Generation with Walk-Jump Sampling A Daigavane, BP Vani, S Saremi, J Kleinhenz, J Rackers arXiv preprint arXiv:2410.14621, 2024 | 1 | 2024 |
| AlphaFold2-RAVE: From sequence to Boltzmann ensemble BP Vani, A Aranganathan, D Wang, P Tiwary | 1 | 2022 |
| Enhancing CAR T cell therapy through in silico modeling of hinge sequence length based on epitope location JM Mirazee, A Aranganathan, S Achar, D Jia, X Chen, BP Vani, CD Chien, ... Biophysical Journal 123 (3), 552a, 2024 | | 2024 |
| Hinging on Success: Leveraging the Power of CAR T-Cell Therapy through In-Silico Modeling of Hinge Length and Epitope Location JM Mirazee, A Aranganathan, S Achar, D Jia, X Chen, B Vani, CD Chien, ... The Journal of Immunology 210 (Supplement_1), 68.06-68.06, 2023 | | 2023 |
| Developing Stratification Methods for the Enhanced Sampling of Rare Events B Vani The University of Chicago, 2021 | | 2021 |
| Molecular Dynamics Simulations of the Circadian Clock Protein Kaic Reveal Structural Insights into the Nucleotide Release and Circadian Timing Mechanisms L Hong, BP Vani, EH Thiede, MJ Rust, AR Dinner Biophysical Journal 116 (3), 310a, 2019 | | 2019 |
