Amarda Shehu, Associate Vice President of Research, Institute for Digital Innovation (IDIA); Associate Dean for AI Innovation (CEC); Professor, Computer Science, received funding for the project: "Collaborative Research: IIBR: Innovation: Bioinformatics: Linking Chemical and Biological Space: Deep Learning and Experimentation for Property-Controlled Molecule Generation."
This project advances property-controlled molecule generation. A key insight propelling property-controlled molecule generation is that machine learning models need to be situated in biological data and knowledge.
The research activities for this project are organized in three thrusts: (1) developing generalizable and interpretable models capable of incorporating biological constraints, (2) accommodating small, incomplete, and noisy wet-laboratory data, and (3) integrating computation and wet-lab inquiry under an active learning formulation.
The project catalyzes synergistic and innovative work at the interface of machine learning, artificial intelligence, generative artificial intelligence, and the biological sciences to address long-standing challenges in molecular biology—both broadly and specifically on particular classes of molecules. The project additionally addresses small disinfectant antimicrobial compounds, where structural innovation has been sorely lacking and resistant bacteria represent an uncountered threat (quaternary ammonium compounds).
The total award amount is $299,320 and Shehu has received $97,078 from the National Science Foundation for this research for FY24. The intended project duration is Aug. 2023 to July 2026.
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