| Deep mendelian randomization: Investigating the causal knowledge of genomic deep learning models S Malina, D Cizin, DA Knowles PLoS computational biology 18 (10), e1009880, 2022 | 4 | 2022 |
| Forecasting labels under distribution-shift for machine-guided sequence design LB Wheelock, S Malina, J Gerold, S Sinai Machine Learning in Computational Biology, 166-180, 2022 | 3 | 2022 |
| Efficient design of optimized AAV capsids using multi-property machine learning models trained across cells, organs and species S Abestesh, I Akartuna, A Brown, M Cramer, F Damani, J Gerold, J Gorns, ... MOLECULAR THERAPY 29 (4), 12-12, 2021 | 1 | 2021 |
| Beyond the training set: an intuitive method for detecting distribution shift in model-based optimization F Damani, DH Brookes, T Sternlieb, C Webster, S Malina, R Jajoo, K Lin, ... arXiv preprint arXiv:2311.05363, 2023 | | 2023 |
| Generative design for gene therapy: An validated method F Damani, D Brookes, J Chan, R Jajoo, A Mijalis, J Samson, F Vadan, ... NeurIPS 2023 Generative AI and Biology (GenBio) Workshop, 2023 | | 2023 |
| Forecasting labels under distribution-shift for machine-guided sequence design L Berk Wheelock, S Malina, J Gerold, S Sinai arXiv e-prints, arXiv: 2211.10422, 2022 | | 2022 |
| Medium-Throughput Characterization of Engineered AAV Transduction Properties in NHP Retina C Sengel, A Shanehsazzadeh, A Wec, C Reardon, E Locane, E Lykken, ... MOLECULAR THERAPY 30 (4), 441-441, 2022 | | 2022 |
| AAV Capsid Property Estimation Is Improved by Combining Single-Molecule ID Tags and Hierarchical Bayesian Modeling of Experimental Processes K Lin, J Otwinowski, B Tobin, S Wolock, J Kwasnieski, C Sengel, R Ogurlu, ... MOLECULAR THERAPY 29 (4), 98-98, 2021 | | 2021 |
| Repcoin: A Market-Based Approach to Reputation SD Malina | | 2015 |
