Michael L. Stitzel

The paper integrates multiple scRNA-seq datasets to create a comprehensive atlas of human pancreatic islets, identifying 13 cell populations and providing a resource for diabetes research.

This study shows that a 6-month lifestyle intervention reduces ER stress and inflammation while enhancing naive immune cell identity in older adults with metabolic disease.

The paper analyzes single-cell transcriptomes of human islet cells across glycemic states to identify gene expression defects in beta cells associated with type 2 diabetes.

This study identifies LONP1's role in mitochondrial protein folding and shows its impact on beta cell survival and hyperglycemia in type 2 diabetes.

The paper models metabolic disease susceptibility and resilience in genetically diverse mice by analyzing diet-induced metabolic responses across three strains.

The paper develops a knowledge graph framework to extract biomedical knowledge from PubMed, creating a database that enhances transparency in biomedical AI applications.

This study investigates how human pancreatic islet cells respond to ER and cytokine stress and identifies T2D-associated genetic variants that modulate these responses.

The paper examines how histone modifications vary across mouse strains and correlates these variations with gene expression, finding strong links between chromatin states and gene expression, but not DNA methylation.

CoRE-ATAC is a deep learning model that classifies regulatory elements from ATAC-seq data, accurately predicting cis-RE functions across multiple cell types and identifying cell-specific variations in regulatory activity.

This paper introduces ATAC-DoubletDetector, a read count-based method to detect multiplets in snATAC-seq data and annotate their cellular origins, achieving 85% accuracy in annotation.

The paper maps transcription start sites in human pancreatic islets and identifies functional regulatory elements linked to type 2 diabetes GWAS signals.

The paper investigates how genetic variants affect gene expression in human pancreatic islets and identifies candidate genes linked to type 2 diabetes.

The paper identifies functional β cell transcriptional variants from T2D GWAS SNPs using MPRA, showing strong correlation with chromatin accessibility and revealing regulatory features under stress conditions.

BiFET improves TF footprint enrichment analysis by correcting biases in chromatin accessibility and GC content, increasing power and reducing false positives.

The paper provides multi-genomic maps of the EndoC-βH1 cell model to define gene regulatory programs in human pancreatic β cells and identifies allelic effects on cis-regulatory elements.

The paper profiles chromatin accessibility in human islets from T2D and non-diabetic individuals to identify genetic and disease-associated changes in cis-regulatory element use.

CellView provides an interactive web tool for exploring high-dimensional single cell RNA-seq data to enhance biological insights.