Rachit Abhigyan

A distribution-aware and functionally relevant novel framework for generation and discovery of bioactive peptides

The proposed two-phase generative–evolutionary framework provides a generalizable approach for balancing functional optimization and distributional realism and can be applied to peptide discovery and data augmentation in imbalanced biological datasets thereby generating high confidence peptides for wet lab validation.