Tyler H. Garvin

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 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.

The paper uses long-read sequencing to analyze structural variations in the SK-BR-3 breast cancer cell line, revealing complex rearrangements and novel gene fusions.