Woo Jun Shim

This study identifies latent regulatory programs from disease-associated variants to reveal biological mechanisms and clinical subtypes in complex diseases.

This study shows glycaemic variability, not just hyperglycaemia, increases heart muscle dysfunction and myocardial injury risk in diabetes using genetic and experimental models.

This study compares sixteen iPSC-CM differentiation protocols to identify how protocol-dependent cell states affect disease modeling capacity for cardiovascular conditions.

This study shows how metabolic culture conditions affect cardiomyocyte maturation and sensitivity to ischaemia-reperfusion injury using hiPSC-CMs.

The paper identifies regions of the human genome under cellular constraint by analyzing chromatin accessibility across cell types, showing their predictive power for functional loci and applications in variant identification and drug discovery.

The paper develops a resource to improve cardiac modelling protocols using hPSC-CMs by analyzing decades of research data and providing tools for protocol benchmarking.

The paper introduces TRIAGE-Cluster and TRIAGE-ParseR to define cell diversity in scRNA-seq data using epigenetic data as a biological anchor.

The paper creates an iPSC differentiation atlas and identifies TMEM88 as a regulator of mesendodermal development and blood pressure.