Jason Grealey

This study evaluates deep learning methods for polygenic prediction, showing that MLP benefits most from larger sample sizes and one-hot encoding improves performance across methods.

This study quantifies the carbon footprint of bioinformatics analyses and identifies strategies to reduce energy consumption and CO2 emissions.

This study compares machine learning and univariate methods for constructing polygenic scores for 26 blood cell traits using UK Biobank and INTERVAL data, showing improved performance with learning methods.