A. Trinh

A Machine Learning Framework for Short Peptide Sequence Optimization

A data-driven, multi-objective peptide design framework that inte-grates sequence-to-feature transformations using Fast Fourier Transform - based representations, and metric-learning based optimization strategies, to provide an interpretable and computationally efficient alternative for peptide design under limited-data constraints.