Mahbuba Tasmin

she/her

Ph.D. Candidate in Computer Science at UMass Amherst. My research integrates machine learning and computational biology to understand and predict antibiotic resistance in Mycobacterium tuberculosis.

FARM: Forecasting Antibiotic Resistance in Mycobacterium tuberculosis Using Biophysics and Machine Learning

Published in bioRxiv (2026); manuscript under review at Proceedings of the National Academy of Sciences (PNAS), 2026

FARM integrates protein structure, Rosetta energetics, evolutionary features, and protein-language-model signals into interpretable models for mutation-level antibiotic resistance prediction, aimed at prioritizing variants of uncertain significance where labeled data is sparse.

Recommended citation: Tasmin, M., Barethiya, S., Wang, Y., Kang, L., Chen, J., Green, A.G. FARM: Forecasting Antibiotic Resistance in Mycobacterium tuberculosis using biophysics and machine learning. bioRxiv (2026).
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