This Project Grant, awarded by the National Science Foundation Division of Information and Intelligent Systems, provides $599,871 to Emory University from August 1, 2023 to July 31, 2026. The funding supports collaborative research at the intersection of machine learning, bioinformatics, and molecular biology. The project aims to advance algorithmic research using principled protein language models (PLMs) to gain deeper insight into the structural, functional, and evolutionary organization of the protein space. Key objectives include encoding prior biological knowledge in PLMs, revealing fundamental properties of the learned representation space, and enabling PLMs to capture diverse contexts for exploring protein space. This interdisciplinary effort contributes to the fields of machine learning, bioinformatics, and molecular biology, while also providing training opportunities for underrepresented students. The research activities are organized across three main thrusts: (1) composite learning with encoded biological priors, (2) representation space analysis, and (3) contextual modeling of protein space.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $599.9k | 7/18/23 |