Oscar Aguilar

The paper presents a unified meta-regression model that identifies epilepsy-associated genes by integrating constraint predictions, pathogenicity scores, and variant annotations from multiple datasets.

The paper trains machine learning models on multi-omics UK Biobank data to predict disease risk, finding metabolomics provides limited improvement over standard features but can replace them when unavailable.