Momoe Kato

The paper identifies hidden enhancers in mouse embryos that are not detected by conventional chromatin profiling methods, highlighting a significant gap in enhancer discovery.

The paper maps the mutagenic sensitivity of human enhancers in vivo by systematically mutating enhancer sequences and using predictive modeling to identify critical nucleotides.

The paper combines massively parallel reporter assays and mouse transgenic assays to study the functional impact of non-coding variants on neuronal enhancer activity, finding strong correlations and additional pleiotropic effects.

The paper identifies 14,000 human craniofacial enhancers across developmental stages and shows 56% are conserved in mice, providing cell type- and stage-specific activity profiles.

The paper identifies widespread epigenomic changes in idiopathic dilated cardiomyopathy, showing a shift toward fetal-like enhancer states and providing a data resource for further study.

This paper develops a cross-organism framework for enhancer prediction using Drosophila STARR-seq data and supervised machine learning, validated in mouse and human with 153 enhancers.

The paper systematically maps chromatin state landscapes during mouse development by profiling histone modifications across 72 tissue-stages, identifying dynamic enhancers and transcriptional regulators.