| Protein complex prediction with AlphaFold-Multimer R Evans, M O’Neill, A Pritzel, N Antropova, A Senior, T Green, A Žídek, ... biorxiv, 2021.10. 04.463034, 2021 | 2739 | 2021 |
| De novo design of protein structure and function with RFdiffusion JL Watson, D Juergens, NR Bennett, BL Trippe, J Yim, HE Eisenach, ... Nature 620 (7976), 1089-1100, 2023 | 1171* | 2023 |
| Predicting conversion to wet age-related macular degeneration using deep learning J Yim, R Chopra, T Spitz, J Winkens, A Obika, C Kelly, H Askham, M Lukic, ... Nature Medicine 26 (6), 892-899, 2020 | 275 | 2020 |
| Diffusion probabilistic modeling of protein backbones in 3d for the motif-scaffolding problem BL Trippe, J Yim, D Tischer, D Baker, T Broderick, R Barzilay, T Jaakkola arXiv preprint arXiv:2206.04119, 2022 | 245 | 2022 |
| SE (3) diffusion model with application to protein backbone generation J Yim, BL Trippe, V De Bortoli, E Mathieu, A Doucet, R Barzilay, ... arXiv preprint arXiv:2302.02277, 2023 | 206 | 2023 |
| Generative flows on discrete state-spaces: Enabling multimodal flows with applications to protein co-design A Campbell, J Yim, R Barzilay, T Rainforth, T Jaakkola arXiv preprint arXiv:2402.04997, 2024 | 77 | 2024 |
| Fast protein backbone generation with se (3) flow matching J Yim, A Campbell, AYK Foong, M Gastegger, J Jiménez-Luna, S Lewis, ... arXiv preprint arXiv:2310.05297, 2023 | 69 | 2023 |
| Sparse projection oblique randomer forests TM Tomita, J Browne, C Shen, J Chung, JL Patsolic, B Falk, CE Priebe, ... Journal of machine learning research 21 (104), 1-39, 2020 | 64 | 2020 |
| Improved motif-scaffolding with SE (3) flow matching J Yim, A Campbell, E Mathieu, AYK Foong, M Gastegger, J Jiménez-Luna, ... ArXiv, arXiv: 2401.04082 v2, 2024 | 30 | 2024 |
| Improving protein optimization with smoothed fitness landscapes A Kirjner, J Yim, R Samusevich, S Bracha, T Jaakkola, R Barzilay, I Fiete arXiv preprint arXiv:2307.00494, 2023 | 26* | 2023 |
| Diffusion models in protein structure and docking J Yim, H Stärk, G Corso, B Jing, R Barzilay, TS Jaakkola Wiley Interdisciplinary Reviews: Computational Molecular Science 14 (2), e1711, 2024 | 23 | 2024 |
| Fast non-autoregressive inverse folding with discrete diffusion JJ Yang, J Yim, R Barzilay, T Jaakkola arXiv preprint arXiv:2312.02447, 2023 | 4 | 2023 |
| Generator Matching: Generative modeling with arbitrary Markov processes P Holderrieth, M Havasi, J Yim, N Shaul, I Gat, T Jaakkola, B Karrer, ... arXiv preprint arXiv:2410.20587, 2024 | 3 | 2024 |
| Predicting disease progression from tissue images and tissue segmentation maps J Yim, RK Chopra, T Spitz, JH Winkens, AAN Obika, T Back, JR Ledsam, ... US Patent 11,935,232, 2024 | 2 | 2024 |
| Integrating Generative and Experimental Platforms for Biomolecular Design CH Liu, J Rector-Brooks, S Yang, SL Lisanza, FZ Li, H Stark, J Gershon, ... ICLR 2025 Workshop Proposals, 2024 | 2 | 2024 |
| Scalable emulation of protein equilibrium ensembles with generative deep learning S Lewis, T Hempel, J Jiménez-Luna, M Gastegger, Y Xie, AYK Foong, ... bioRxiv, 2024.12. 05.626885, 2024 | 1 | 2024 |
| Diffusion Probabilistic Modeling of Protein Backbones in 3D for the Motif-Scaffolding problem J Yim Massachusetts Institute of Technology, 2023 | 1 | 2023 |
| Quantitative analysis of change in retinal tissues in neovascular age-related macular degeneration using artificial intelligence R Chopra, G Moraes, DJ Fu, S Wagner, T Spitz, M Wilson, J Yim, ... Investigative Ophthalmology & Visual Science 61 (7), 1152-1152, 2020 | 1 | 2020 |
| MotifBench: A standardized protein design benchmark for motif-scaffolding problems Z Zheng, B Zhang, K Didi, KK Yang, J Yim, JL Watson, HF Chen, ... arXiv preprint arXiv:2502.12479, 2025 | | 2025 |
| Predicting protein amino acid sequences using generative models conditioned on protein structure embeddings AW Senior, S Kohl, J Yim, RJ Bates, CD Ionescu, CTC Nash, ... US Patent App. 18/275,933, 2024 | | 2024 |
Tommi JaakkolaMITยืนยันอีเมลแล้วที่ csail.mit.edu