Ran Elkon

The paper identifies a rare subpopulation of cochlear supporting cells that transdifferentiate into hair cells upon Notch inhibition, revealing epigenetic and transcriptional changes associated with this process.

This paper maps GWAS risk variants to relevant cellular contexts using deep learning and biological ontologies to interpret genetic associations.

The paper identifies H1 histone variants as regulators of transcriptional programs in autism with 16p11.2 deletion, showing their upregulation and link to MAZ.

This study evaluates how imputation panels affect polygenic risk score accuracy across different ethnic populations, finding only marginal improvements when panels match the target population.

The paper introduces a web-server for the DOMINO algorithm, which identifies active modules in gene networks and provides tools for analysis and interpretation.

CT-FOCS infers cell type-specific enhancer-promoter links using linear mixed effect models and outperforms existing methods on FANTOM5 data.

The paper develops a method to deconvolve cell-type mixtures using enhancer-promoter methylation profiles from long-read data, achieving higher accuracy than promoter-based approaches.

The paper introduces DOMINO, a novel algorithm for identifying active modules in omics data, which outperforms existing methods by reducing false calls through permutation-based significance evaluation.

The paper identifies 2,305 SNPs that disrupt 3’ UTR polyadenylation signals and links them to gene expression, eQTLs, and GWAS traits.

The paper identifies and characterizes four lncRNAs in the mouse cochlea, showing their expression patterns and potential roles in inner ear function.

The paper performs a meta-analysis of Hi-C, ChIP-seq, and RNA-seq data to show how 3D chromatin organization influences gene expression in different cell types under basal and stress conditions.

The paper introduces FOCS, a method to infer enhancer-promoter links using activity patterns, and presents an extensive E-P map covering over 300,000 links.