Eldon G. Emberly

The paper develops a motif-based model to predict sequence variant effects in AR enhancers and identifies functional classes of transcription factors, validated against mutagenesis data and GWAS risk alleles.

This study uses mathematical modeling to investigate the multifactorial causes of anabolic resistance in sarcopenia and evaluates therapeutic strategies to restore muscle protein metabolism.

The paper infers enhancer-specific transcription factor interactions from gene expression data using a biophysical model and validates it with simulated and experimental data.

The paper introduces a method to infer functional regulatory sites in enhancer sequences using STARR-seq data, showing it can identify local regulatory sites missed by global approaches.

The paper identifies neural signatures of resource-based and resistance-based cognitive control in rats during delay discounting tasks using electrophysiological recordings.

This study shows that ACC neuron ensembles undergo abrupt, coordinated changes in representing rewarded and nonrewarded levers when rats transition from exploration to exploitation.