Zhana Duren

Contrasting within-donor gene covariation identifies disease-associated cells and genes in case-control single-cell studies

Resolving how genetic perturbations act through gene regulatory paths

REGA-perturb resolves gene regulatory paths from genetic perturbations using reference epigenomes and RNA measurements, outperforming existing methods in identifying TF-target relationships and predicting regulatory changes.

Reference Regulatory Element-Guided Gene Expression Analysis for Mechanistic Inference of Gene Regulatory Networks

This paper introduces REGA, a framework that uses reference regulatory elements to infer gene regulatory networks from expression data, showing improved performance across multiple benchmarks and applications.

Epiregulon: Inference of single-cell transcription factor activity to predict drug response and drivers of cell state

Epiregulon infers single-cell TF activity using ATAC-seq and RNA-seq to predict drug response and identify drivers of cell state.

Integrated Single-Cell Multiomic Profiling of Caudate Nucleus Suggests Key Mechanisms in Alcohol Use Disorder

The paper uses multiomic profiling of the caudate nucleus to identify gene expression and chromatin changes in AUD, linking them to risk genes through QTL analysis.

Continuous lifelong learning for modeling of gene regulation from single cell multiome data by leveraging atlas-scale external data

LINGER improves GRN inference from single-cell multiome data by integrating atlas-scale bulk data and TF motif knowledge, achieving 2-3 fold higher accuracy.

Heritability enrichment in context-specific regulatory networks improves phenotype-relevant tissue identification

SpecVar improves heritability enrichment by integrating regulatory networks with GWAS data to identify relevant tissues and shared heritability.

Human genetic variants associated with COVID-19 severity are enriched in immune and epithelium regulatory networks

Dynamic chromatin regulatory landscape of human CAR T cell exhaustion

The paper examines dynamic chromatin changes in human CAR T cells during exhaustion, identifying regulatory networks and enhancer roles in exhaustion-associated genes.

Modeling regulatory network topology improves genome-wide analyses of complex human traits

This paper develops a Bayesian framework integrating GWAS with regulatory networks to improve the identification of trait-associated genes by modeling network topology.

GuidingNet: revealing transcriptional cofactor and predicting binding for DNA methyltransferase by network regularization

GuidingNet predicts DNA methyltransferase genome-wide binding by integrating multi-omics data and reveals transcriptional cofactors involved in methylation.

Tyrosine kinase inhibitors induce mitochondrial dysfunction during cardiomyocyte differentiation through alteration of GATA4-mediated networks

This study shows that tyrosine kinase inhibitors cause mitochondrial dysfunction in cardiomyocytes by altering GATA4-mediated networks, and GATA4 overexpression can rescue these effects.

Joint Inference of Clonal Structure using Single-cell Genome and Transcriptome Sequencing Data

This study introduces CC-NMF, a framework that jointly infers clonal structure from matched scDNA and scRNA data, showing robustness and accuracy in resolving genomic and transcriptomic clonal architecture.

Integrative analysis of single cell genomics data by coupled nonnegative matrix factorizations

The paper introduces coupled nonnegative matrix factorizations to integrate single cell RNA-seq and ATAC-seq data by coupling clustering across samples.

Feedback Regulation between Initiation and Maturation Networks Orchestrates the Chromatin Dynamics of Epidermal Lineage Commitment

The paper identifies TFAP2C and p63 as key regulators of epidermal lineage commitment and shows TFAP2C initiates differentiation while p63 drives maturation through chromatin dynamics.

Unsupervised clustering and epigenetic classification of single cells

This paper introduces scABC, an R package for unsupervised clustering of scATAC-seq data to classify cell types based on open chromatin regions.