| Positive-unlabeled convolutional neural networks for particle picking in cryo-electron micrographs T Bepler, A Morin, M Rapp, J Brasch, L Shapiro, AJ Noble, B Berger Nature methods 16 (11), 1153-1160, 2019 | 854 | 2019 |
| CryoDRGN: reconstruction of heterogeneous cryo-EM structures using neural networks ED Zhong, T Bepler, B Berger, JH Davis Nature methods 18 (2), 176-185, 2021 | 448 | 2021 |
| Learning protein sequence embeddings using information from structure T Bepler, B Berger 7th International Conference on Learning Representations, ICLR 2019, New …, 2019 | 324 | 2019 |
| Topaz-Denoise: general deep denoising models for cryoEM and cryoET T Bepler, K Kelley, AJ Noble, B Berger Nature communications 11 (1), 1-12, 2020 | 319 | 2020 |
| Learning the protein language: Evolution, structure, and function T Bepler, B Berger Cell systems 12 (6), 654-669. e3, 2021 | 294 | 2021 |
| Human-chimpanzee differences in a FZD8 enhancer alter cell-cycle dynamics in the developing neocortex JL Boyd, SL Skove, JP Rouanet, LJ Pilaz, T Bepler, R Gordân, GA Wray, ... Current Biology 25 (6), 772-779, 2015 | 267 | 2015 |
| Reconstructing continuous distributions of 3D protein structure from cryo-EM images ED Zhong, T Bepler, JH Davis, B Berger arXiv preprint arXiv:1909.05215, 2019 | 102 | 2019 |
| Explicitly disentangling image content from rotation and translation with spatial-VAE T Bepler, E Zhong, K Kelley, E Brignole, B Berger Neural Informational Processing Systems (NeurIPS), 2019 | 97* | 2019 |
| Visualization of clustered protocadherin neuronal self-recognition complexes J Brasch, KM Goodman, AJ Noble, M Rapp, S Mannepalli, F Bahna, ... Nature 569 (7755), 280-283, 2019 | 92 | 2019 |
| Divergence in DNA specificity among paralogous transcription factors contributes to their differential in vivo binding N Shen, J Zhao, JL Schipper, Y Zhang, T Bepler, D Leehr, J Bradley, ... Cell systems 6 (4), 470-483. e8, 2018 | 55 | 2018 |
| Distinct routes to metastasis: plasticity-dependent and plasticity-independent pathways JA Somarelli, D Schaeffer, MS Marengo, T Bepler, D Rouse, KE Ware, ... Oncogene 35 (33), 4302-4311, 2016 | 50 | 2016 |
| Machine learning optimization of candidate antibody yields highly diverse sub-nanomolar affinity antibody libraries L Li, E Gupta, J Spaeth, L Shing, R Jaimes, E Engelhart, R Lopez, ... Nature Communications 14 (1), 3454, 2023 | 33 | 2023 |
| An engineered protein-phosphorylation toggle network with implications for endogenous network discovery D Mishra, T Bepler, B Teague, B Berger, J Broach, R Weiss Science 373 (6550), eaav0780, 2021 | 28 | 2021 |
| Synthetic molecular evolution of antimicrobial peptides CH Chen, T Bepler, K Pepper, D Fu, TK Lu Current opinion in biotechnology 75, 102718, 2022 | 25 | 2022 |
| Latent Representations of Phylogeny to Predict Organism Phenotype JN Oppenheim, T Bepler US Patent App. 16/170,993, 2019 | 19 | 2019 |
| Fully automated multi-grid cryoEM screening using Smart Leginon A Cheng, PT Kim, H Kuang, JH Mendez, EYD Chua, K Maruthi, H Wei, ... IUCrJ 10 (1), 77-89, 2023 | 18 | 2023 |
| Learning to automate cryo-electron microscopy data collection with Ptolemy PT Kim, AJ Noble, A Cheng, T Bepler IUCrJ 10 (1), 90-102, 2023 | 17 | 2023 |
| TOPAZ: A positive-unlabeled convolutional neural network CryoEM particle picker that can pick any size and shape particle T Bepler, A Morin, M Rapp, J Brasch, L Shapiro, AJ Noble, B Berger Microscopy and Microanalysis 25 (S2), 986-987, 2019 | 17 | 2019 |
| PoET: A generative model of protein families as sequences-of-sequences T Truong Jr, T Bepler Advances in Neural Information Processing Systems 36, 2023 | 12 | 2023 |
| Unsupervised Object Representation Learning using Translation and Rotation Group Equivariant VAE A Nasiri, T Bepler Advances in Neural Information Processing Systems, 2022 | 10 | 2022 |
