Thomas Scott Brettin

This paper develops a spatio-temporal analysis framework to uncover coupled mutagenic mechanisms in radiation-induced genomic instability using whole-genome sequencing data from irradiated human cells.

The paper models how low-dose radiation affects nuclear morphology by linking RNA-seq data to cell-painting imaging features over time using an interpretable inverse modeling framework.

BrainXcan uses genetic and imaging data to identify brain features linked to psychiatric traits, finding reduced axonal density and hippocampal features associated with schizophrenia risk.

This paper addresses data imbalance in drug response prediction by introducing a multi-objective optimization approach using a custom loss function to improve model performance.

GenSLMs use large language models to analyze SARS-CoV-2 genomes, enabling rapid identification of variants of concern and providing insights into evolutionary dynamics.

Open-source KBase platform unites reference genomes and biochemistry, over 70 apps, Jupyter-based Narratives with provenance, and a Docker SDK for reproducible plant and microbial systems biology.

This study develops an XGBoost-based machine learning model to predict minimum inhibitory concentrations for 20 antibiotics in Klebsiella pneumoniae using whole genome sequencing data, achieving 92% overall accuracy.