Cleo C. van Diemen

DAVE uses explainable AI to interpret missense variants by integrating biophysically grounded features, improving variant classification and interpretability for genome diagnostics.

The paper identifies enhancer regions of SCA genes in human cerebellum and screens for copy number variants in undiagnosed patients, finding one potential CNV of unknown significance.

This study uses Cas9-directed long-read sequencing to validate and refine optical genome mapping findings in leukemia diagnostics, improving breakpoint resolution and clinical relevance assessment.

CAPICE is a machine learning method that prioritizes pathogenic variants in exomes, outperforming existing tools for rare and ultra-rare variants.

This paper introduces GADO, a tool that uses gene expression data to predict gene-phenotype associations and improve diagnostic yield in exome sequencing by prioritizing variants in patients with unknown genetic diagnoses.