Debora Marks, PhD
Affiliations: | 2014- | Systems Biology | Harvard Medical School |
Area:
computational biologyWebsite:
https://www.deboramarkslab.com/Google:
"Debora Marks"Parents
Sign in to add mentor| Hanspeter Herzel | grad student | 2007-2010 | Humboldt University Berlin (Neurotree) |
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Publications
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| Notin P, Rollins N, Gal Y, et al. (2024) Machine learning for functional protein design. Nature Biotechnology. 42: 216-228 |
| Peidli S, Green TD, Shen C, et al. (2024) scPerturb: harmonized single-cell perturbation data. Nature Methods |
| Thadani NN, Gurev S, Notin P, et al. (2023) Learning from prepandemic data to forecast viral escape. Nature. 622: 818-825 |
| Fram B, Truebridge I, Su Y, et al. (2023) Simultaneous enhancement of multiple functional properties using evolution-informed protein design. Biorxiv : the Preprint Server For Biology |
| Placido D, Yuan B, Hjaltelin JX, et al. (2023) A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories. Nature Medicine |
| Shin JE, Riesselman AJ, Kollasch AW, et al. (2021) Protein design and variant prediction using autoregressive generative models. Nature Communications. 12: 2403 |
| Yuan B, Shen C, Luna A, et al. (2020) CellBox: Interpretable Machine Learning for Perturbation Biology with Application to the Design of Cancer Combination Therapy. Cell Systems |
| Shen J, Yuan B, Luna A, et al. (2020) Abstract 2102: Interpretable machine learning for perturbation biology Cancer Research. 80: 2102-2102 |
| Stiffler MA, Poelwijk FJ, Brock KP, et al. (2019) Protein Structure from Experimental Evolution. Cell Systems |
| Rollins NJ, Brock KP, Poelwijk FJ, et al. (2019) Inferring protein 3D structure from deep mutation scans. Nature Genetics |