| 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 | 489* | 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 | 361 | 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 | 76* | 2022 |
| Computationally designed proteins mimic antibody immune evasion in viral evolution N Youssef, S Gurev, F Ghantous, KP Brock, JA Jaimes, NN Thadani, ... Immunity, 2025 | 24* | 2025 |
| Proteome-wide model for human disease genetics R Orenbuch, CA Shearer, AW Kollasch, AD Spinner, T Hopf, ... Nature Genetics 57, 3165-3174, 2025 | 22* | 2025 |
| 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 | 16 | 2024 |
| Combining structure and sequence for superior fitness prediction S Paul, A Kollasch, P Notin, D Marks NeurIPS 2023 Generative AI and Biology (GenBio) Workshop, 2023 | 7 | 2023 |
| Rnagym: Large-scale benchmarks for rna fitness and structure prediction R Arora, M Angelo, CA Choe, CA Shearer, AW Kollasch, F Qu, ... bioRxiv, 2025.06. 16.660049, 2025 | 5* | 2025 |
| Breaking through biology’s data wall: expanding the known tree of life by over 10x using a global biodiscovery pipeline O Vince, P Oldach, V Pereno, MHY Leung, C Greco, G Minto-Cowcher, ... bioRxiv, 2025.06. 11.658620, 2025 | 3 | 2025 |
| High-Throughput Machine Learning-Aided Antibody Discovery for Cell Surface Antigens D Kothiwal, AW Kollasch, N Hollmer, A Ghosh, R Zhang, M Anuganti, ... bioRxiv, 2025.05. 15.650607, 2025 | 2 | 2025 |
| 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 |
| Designing AI-programmable therapeutics with the EDEN family of foundation models G Munsamy, G Ayres, C Greco, K Kam, G Minto-Cowcher, J St John, ... bioRxiv, 2026.01. 12.699009, 2026 | | 2026 |
| Machine Learning enables efficient and effective affinity maturation of nanobodies SB Paul, EP Harvey, J Osei-Owusu, AW Kollasch, AJ Riesselman, ... bioRxiv, 2026.01. 11.698911, 2026 | | 2026 |
| Few-shot Protein Fitness Prediction via In-context Learning and Test-time Training F Teufel, AW Kollasch, Y Huang, O Winther, KK Yang, P Notin, DS Marks arXiv preprint arXiv:2512.02315, 2025 | | 2025 |
| debbiemarkslab/SeqDesign: SeqDesign public code, data JE Shin, A Riesselman, A Kollasch Zenodo, 0 | | |
