Joseph M. Paggi

The paper develops a simulation framework to infer nucleosome-resolution chromatin structures from RCMC data, revealing euchromatin as condensed domains with accessible promoter/enhancer regions.

This study identifies a non-canonical mechanism of GPCR activation where agonists directly rearrange an intracellular loop to regulate signaling, with implications for drug design.

This study uses deep mutational scanning to analyze GPCR variants, identifying key residues for signaling and function across multiple GPCR classes.

The paper identifies 138 associations between common protein-altering variants in GPCR genes and various phenotypes using UK Biobank data.

S-CAP improves pathogenicity prediction for splicing-relevant variants by reducing uncertain variants by 41% with 95% sensitivity.

This paper introduces a deep learning model, LaBranchoR, that predicts RNA splicing branchpoints with high accuracy, showing better reliability than existing annotations.

The paper identifies hundreds of novel recursive splicing sites in Drosophila introns, showing they are more accurately spliced and often located in long introns involved in development.

HISAT-genotype improves variant analysis accuracy for HLA typing and DNA fingerprinting by incorporating a comprehensive variant catalog into a memory-efficient alignment framework.