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| InterPro in 2022 T Paysan-Lafosse, M Blum, S Chuguransky, T Grego, BL Pinto, ... Nucleic acids research 51 (D1), D418-D427, 2023 | 1748 | 2023 |
| Protein 3D structure computed from evolutionary sequence variation DS Marks, LJ Colwell, R Sheridan, TA Hopf, A Pagnani, R Zecchina, ... PloS one 6 (12), e28766, 2011 | 1278 | 2011 |
| Three-dimensional structures of membrane proteins from genomic sequencing TA Hopf, LJ Colwell, R Sheridan, B Rost, C Sander, DS Marks Cell 149 (7), 1607-1621, 2012 | 598 | 2012 |
| Using deep learning to annotate the protein universe ML Bileschi, D Belanger, DH Bryant, T Sanderson, B Carter, D Sculley, ... Nature Biotechnology 40 (6), 932-937, 2022 | 301 | 2022 |
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| The interface of protein structure, protein biophysics, and molecular evolution DA Liberles, SA Teichmann, I Bahar, U Bastolla, J Bloom, ... Protein Science 21 (6), 769-785, 2012 | 244 | 2012 |
| Comparative analysis of nanobody sequence and structure data LS Mitchell, LJ Colwell Proteins: Structure, Function, and Bioinformatics 86 (7), 697-706, 2018 | 215 | 2018 |
| Predicting multiple conformations via sequence clustering and AlphaFold2 HK Wayment-Steele, A Ojoawo, R Otten, JM Apitz, W Pitsawong, ... Nature 625 (7996), 832-839, 2024 | 213 | 2024 |
| MGnify: the microbiome sequence data analysis resource in 2023 L Richardson, B Allen, G Baldi, M Beracochea, ML Bileschi, T Burdett, ... Nucleic acids research 51 (D1), D753-D759, 2023 | 212 | 2023 |
| Computational approaches to therapeutic antibody design: established methods and emerging trends RA Norman, F Ambrosetti, AMJJ Bonvin, LJ Colwell, S Kelm, S Kumar, ... Briefings in bioinformatics 21 (5), 1549-1567, 2020 | 201 | 2020 |
| Model-based reinforcement learning for biological sequence design C Angermueller, D Dohan, D Belanger, R Deshpande, K Murphy, ... International conference on learning representations, 2019 | 154 | 2019 |
| Evaluating attribution for graph neural networks B Sanchez-Lengeling, J Wei, B Lee, E Reif, P Wang, W Qian, ... Advances in neural information processing systems 33, 5898-5910, 2020 | 150 | 2020 |
| Inferring interaction partners from protein sequences AF Bitbol, RS Dwyer, LJ Colwell, NS Wingreen Proceedings of the National Academy of Sciences 113 (43), 12180-12185, 2016 | 146 | 2016 |
| A core subunit of Polycomb repressive complex 1 is broadly conserved in function but not primary sequence LY Beh, LJ Colwell, NJ Francis Proceedings of the National Academy of Sciences 109 (18), E1063-E1071, 2012 | 133 | 2012 |
| Analysis of nanobody paratopes reveals greater diversity than classical antibodies LS Mitchell, LJ Colwell Protein Engineering, Design and Selection 31 (7-8), 267-275, 2018 | 130 | 2018 |
| ProteInfer, deep neural networks for protein functional inference T Sanderson, ML Bileschi, D Belanger, LJ Colwell Elife 12, e80942, 2023 | 129 | 2023 |
| Charge as a selection criterion for translocation through the nuclear pore complex LJ Colwell, MP Brenner, K Ribbeck PLoS computational biology 6 (4), e1000747, 2010 | 114 | 2010 |
| Rapid discovery and evolution of orthogonal aminoacyl-tRNA synthetase–tRNA pairs D Cervettini, S Tang, SD Fried, JCW Willis, LFH Funke, LJ Colwell, ... Nature Biotechnology 38 (8), 989-999, 2020 | 113 | 2020 |
| Masked language modeling for proteins via linearly scalable long-context transformers K Choromanski, V Likhosherstov, D Dohan, X Song, A Gane, T Sarlos, ... arXiv preprint arXiv:2006.03555, 2020 | 111 | 2020 |
