Vivek Naranbhai

PSICHIC+ is a bioactivity foundation model that predicts binding affinities from sequence data, improving hit identification and hit-to-lead optimization using heterogeneous bioactivity data.

The paper introduces molecular COUPLrs to systematically target protein complexes, identifying new glue classes and their interactions in cancer cell lines.

The paper identifies four genome-wide significant loci affecting monocyte cytokine release and links genetic variants to cytokine secretion patterns.

The paper introduces a modification to cryo-FIB milling patterns by adding fillets to reduce stress concentration and lamella breakage, improving yield by 33%.

This study evaluates alignment-free methods for viral sequence classification, showing high accuracy and efficiency on SARS-CoV-2, dengue, and HIV datasets.

Craft is a machine learning framework for dengue subtyping that achieves high accuracy and speed, outperforming existing tools in classification efficiency.

The paper identifies eQTL specific to NK cells and links them to autoimmunity through transcriptome-wide association studies.

This study identifies three germline variants associated with immune-related adverse events in patients treated with immune checkpoint inhibitors.