Rishab Pulugurta

DPAC predicts and designs protein-DNA interactions using sequence-based contrastive learning, outperforming structure-based methods in speed and accuracy.

This paper introduces FusOn-pLM, a protein language model fine-tuned on fusion oncoprotein sequences using a novel masked language modeling strategy, improving performance on specific benchmarks and disorder prediction tasks.

AMP-Diffusion generates functional antimicrobial peptides using a latent diffusion model integrated with the ESM-2 protein language model, showing alignment with experimentally validated AMPs in pseudo-perplexity and physicochemical properties.