Drug repurposing—identifying new therapeutic uses for approved drugs—is often a
serendipitous and opportunistic endeavour to expand the use of drugs for new diseases …

Over 90% of drug candidates fail in clinical trials, while it takes 10–15 years and one billion
US dollars to develop a single successful drug. Drug development is more challenging for …

Of the several thousand diseases that affect humans, only about 500 have treatments
approved by the US Food and Drug Administration. Even for those with approved …

Identifying genetic drivers of chronic diseases is necessary for drug discovery. Here, we
develop a machine learning-assisted genetic priority score, which we call ML-GPS, that …

Whole genome sequences (WGS) enable discovery of rare variants which may contribute to
missing heritability of coronary artery disease (CAD). To measure their contribution, we …

Birth cohort studies involve repeated surveys of large numbers of individuals from birth and
throughout their lives. They collect information useful for a wide range of life course research …

Choosing which drug targets to pursue for a given disease is one of the most impactful
decisions made in the global development of new medicines. This study examines the …

Discerning the mechanisms driving type 2 diabetes (T2D) pathophysiology from genome-
wide association studies (GWAS) remains a challenge. To this end, we integrated omics …

Machine learning has significantly improved inverse modeling for groundwater systems.
One promising development is the tandem neural network architecture (TNNA), which …

Standard genome-wide association studies (GWAS) and rare variant burden tests are
essential tools for identifying trait-relevant genes. Although these methods are conceptually …