| Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype D Kim, JM Paggi, C Park, C Bennett, SL Salzberg Nature biotechnology 37 (8), 907-915, 2019 | 8336 | 2019 |
| Structure of the µ-opioid receptor–Gi protein complex A Koehl, H Hu, S Maeda, Y Zhang, Q Qu, JM Paggi, NR Latorraca, ... Nature 558 (7711), 547-552, 2018 | 653 | 2018 |
| Structural and functional characterization of G protein–coupled receptors with deep mutational scanning EM Jones, NB Lubock, AJ Venkatakrishnan, J Wang, AM Tseng, JM Paggi, ... Elife 9, e54895, 2020 | 117 | 2020 |
| Crystal structure of the natural anion-conducting channelrhodopsin GtACR1 YS Kim, HE Kato, K Yamashita, S Ito, K Inoue, C Ramakrishnan, ... Nature 561 (7723), 343-348, 2018 | 115 | 2018 |
| Structural basis for channel conduction in the pump-like channelrhodopsin ChRmine KE Kishi, YS Kim, M Fukuda, M Inoue, T Kusakizako, PY Wang, ... Cell 185 (4), 672-689. e23, 2022 | 101 | 2022 |
| Structural mechanisms of selectivity and gating in anion channelrhodopsins HE Kato, YS Kim, JM Paggi, KE Evans, WE Allen, C Richardson, K Inoue, ... Nature 561 (7723), 349-354, 2018 | 93 | 2018 |
| A sequence-based, deep learning model accurately predicts RNA splicing branchpoints JM Paggi, G Bejerano Rna 24 (12), 1647-1658, 2018 | 88 | 2018 |
| Insights into distinct signaling profiles of the µOR activated by diverse agonists Q Qu, W Huang, D Aydin, JM Paggi, AB Seven, H Wang, S Chakraborty, ... Nature chemical biology 19 (4), 423-430, 2023 | 72 | 2023 |
| S-CAP extends pathogenicity prediction to genetic variants that affect RNA splicing KA Jagadeesh, JM Paggi, JS Ye, PD Stenson, DN Cooper, JA Bernstein, ... Nature genetics 51 (4), 755-763, 2019 | 63 | 2019 |
| SL Salzberg Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype., 2019, 37 D Kim, JM Paggi, C Park, C Bennett DOI: https://doi. org/10.1038/s41587-019-0201-4, 907-915, 0 | 56 | |
| Molecular mechanism of biased signaling at the kappa opioid receptor A El Daibani, JM Paggi, K Kim, YD Laloudakis, P Popov, SM Bernhard, ... Nature communications 14 (1), 1338, 2023 | 46 | 2023 |
| Identification of new branch points and unconventional introns in Saccharomyces cerevisiae GM Gould, JM Paggi, Y Guo, DV Phizicky, B Zinshteyn, ET Wang, ... RNA 22 (10), 1522-1534, 2016 | 38 | 2016 |
| Leveraging nonstructural data to predict structures and affinities of protein–ligand complexes JM Paggi, JA Belk, SA Hollingsworth, N Villanueva, AS Powers, MJ Clark, ... Proceedings of the National Academy of Sciences 118 (51), e2112621118, 2021 | 29* | 2021 |
| Numerous recursive sites contribute to accuracy of splicing in long introns in flies AA Pai, JM Paggi, P Yan, K Adelman, CB Burge PLoS Genetics 14 (8), e1007588, 2018 | 26 | 2018 |
| Hisat-genotype: Next generation genomic analysis platform on a personal computer D Kim, J Paggi, SL Salzberg BioRxiv, 266197, 2018 | 22 | 2018 |
| Structural basis for ion selectivity in potassium-selective channelrhodopsins S Tajima, YS Kim, M Fukuda, YJ Jo, PY Wang, JM Paggi, M Inoue, ... Cell 186 (20), 4325-4344. e26, 2023 | 17 | 2023 |
| Geometric deep learning for structure-based ligand design AS Powers, HH Yu, P Suriana, RV Koodli, T Lu, JM Paggi, RO Dror ACS Central Science 9 (12), 2257-2267, 2023 | 16 | 2023 |
| The art and science of molecular docking JM Paggi, A Pandit, RO Dror Annual Review of Biochemistry 93, 2024 | 9 | 2024 |
| Predicting transcriptional regulatory activities with deep convolutional networks J Paggi, A Lamb, K Tian, I Hsu, PL Cedoz, P Kawthekar BioRxiv, 099879, 2017 | 6 | 2017 |
| FlexVDW: A machine learning approach to account for protein flexibility in ligand docking P Suriana, JM Paggi, RO Dror arXiv preprint arXiv:2303.11494, 2023 | 4 | 2023 |
