| Protein design and variant prediction using autoregressive generative models JE Shin, AJ Riesselman, AW Kollasch, C McMahon, E Simon, C Sander, ... Nature communications 12 (1), 2403, 2021 | 398* | 2021 |
| ProteinGym: Large-scale benchmarks for protein fitness prediction and design P Notin, AW Kollasch, D Ritter, L Van Niekerk, S Paul, H Spinner, ... Thirty-seventh Conference on Neural Information Processing Systems Datasets …, 2023 | 140* | 2023 |
| TranceptEVE: Combining family-specific and family-agnostic models of protein sequences for improved fitness prediction P Notin, L Van Niekerk, AW Kollasch, D Ritter, Y Gal, DS Marks bioRxiv, 2022.12. 07.519495, 2022 | 36 | 2022 |
| Deep generative modeling of the human proteome reveals over a hundred novel genes involved in rare genetic disorders R Orenbuch, AW Kollasch, HD Spinner, CA Shearer, TA Hopf, ... Medrxiv, 2023 | 9 | 2023 |
| An ANXA11 P93S variant dysregulates TDP-43 and causes corticobasal syndrome A Snyder, VH Ryan, J Hawrot, S Lawton, DM Ramos, YA Qi, KR Johnson, ... Alzheimer's & Dementia 20, 5220–5235, 2024 | 4 | 2024 |
| Protein design for evaluating vaccines against future viral variation N Youssef, S Gurev, F Ghantous, K Brock, J Jaimes, NN Thadani, ... bioRxiv, 2023.10. 08.561389, 2023 | 4* | 2023 |
| Combining Structure and Sequence for Superior Fitness Prediction S Paul, A Kollasch, P Notin, D Marks NeurIPS 2023 Generative AI and Biology (GenBio) Workshop, 0 | 3 | |
| How well do generative protein models generate? H Spinner, AW Kollasch, DS Marks ICLR 2024 Workshop on Generative and Experimental Perspectives for …, 2024 | 1 | 2024 |
| Large language models for biological prediction and design AW Kollasch Harvard University, 2023 | 1 | 2023 |
