Brendan Michael Reardon

This study evaluates agentic AI's ability to support biological discovery in autonomous and human-AI copilot settings using multi-omic cancer datasets.

The paper identifies genomic features associated with response or resistance to Gem/Doce in BCG-unresponsive NMIBC using whole-exome sequencing and phylogenetic analysis.

The paper introduces Cat-VRS, a framework for computable representation of genomic variant categories to improve data interoperability and clinical interpretation.

This study identifies germline rare variants associated with clear and non-clear cell RCC, accounting for population stratification, and finds distinct risk patterns and somatic associations.

This paper reports a case where platinum chemotherapy exposure was linked to the development of aggressive thyroid cancer through mutational signatures and genomic analysis.

CoMut creates customizable comutation plots from user data to visualize genomic and phenotypic relationships in patient cohorts.

This study identifies novel cancer driver genes by analyzing mutation nucleotide contexts in whole-exome sequencing data from 12,004 tumors.

The paper identifies ATM and PALB2 as CRC risk genes through germline mutation analysis and highlights homologous recombination deficiency in CRC tumors.