Kirstine Ravn

Unsupervised learning of multi-omics data enables disease risk prediction in the UK Biobank

The paper applies a variational autoencoder to multi-omics data from the UK Biobank to assess disease risk prediction and the impact of preprocessing on model performance.

Non-linear genetic regulation of the blood plasma proteome

The paper identifies non-linear genetic regulation of plasma proteins using a deep learning method, finding dominance and epistasis effects in large cohorts.

Tracing the evolutionary path of the CCR5delta32 deletion via ancient and modern genomes

The paper traces the evolutionary history of the CCR5delta32 deletion using ancient and modern genomes, finding it originated at least 7,000 years ago in Western Eurasia and underwent positive selection.

Improved prediction of blood biomarkers using deep learning

This study uses deep learning to predict blood and urine biomarkers from genetic data, outperforming linear methods and capturing non-linear and epistatic effects.