Michael T. Hallett

The paper introduces Murmurent, an agentic AI environment that supports biomedical research collaboration by providing infrastructure, specialized agents, memory, traceability, SOP enforcement, and multi-user capacity.

The paper introduces PREFFECT, a probabilistic framework to improve analysis of FFPE-derived RNA-seq data by addressing transcript dropout and variance through generative models and graph attention mechanisms.

This study identifies genetic alterations associated with recurrence and radiotherapy response in ductal carcinoma in situ using whole-exome sequencing and copy number analysis.

This study profiles single-cell transcriptomes of Candida albicans exposed to antifungal drugs to identify epigenetic responses linked to drug resistance evolution.

The paper introduces a reproducible data analysis system for precision medicine, demonstrating its use in analyzing cancer genomic data.

The paper identifies SNPs associated with mammographic density and breast cancer risk by integrating SNP analyses with mRNA expression and hormone levels.

The paper presents a microservice-based framework for building interactive data exploration tools in systems biology, demonstrating it with a breast cancer transcriptional analysis web application.