David M. Herrington

Systematic Integration of genomics with transcriptomics for the Study of Coronary Artery Disease and Subclinical Atherosclerosis

This study integrates CAD GWAS with transcriptomic data to identify genes and networks associated with CAD and subclinical atherosclerosis.

ABDS: tool suite for analyzing biologically diverse samples

ABDS provides tools for analyzing biologically diverse samples by addressing missing value imputation, signature gene detection, and expression pattern visualization.

swCAM: estimation of subtype-specific expressions in individual samples with unsupervised sample-wise deconvolution

swCAM estimates subtype-specific expressions in individual samples using unsupervised deconvolution, revealing changes in cell proportions and gene expression in bipolar disorder.

Contrasting Effects of Western vs. Mediterranean Diets on Monocyte Inflammatory Gene Expression and Social Behavior in a Primate Model

This study examines how Western and Mediterranean diets affect monocyte gene expression and social behavior in macaques, finding proinflammatory gene changes and behavioral differences.

Determining molecular archetype composition and expression from bulk tissues with unsupervised deconvolution

This paper introduces an unsupervised deconvolution method, CAM3.0, to determine molecular archetype composition and expression from bulk tissues, showing its effectiveness through simulations and case studies.

DDN2.0: R and Python packages for differential dependency network analysis of biological systems

DDN2.0 provides R and Python tools for differential dependency network analysis to identify key pathways and network rewiring across omics data.

Data-driven detection of subtype-specific and differentially expressed genes

This paper introduces OVE-FC and OVE-sFC tests to detect subtype-specific and differentially expressed genes, showing improved accuracy in deconvolution compared to existing methods.

COT: an efficient Python tool for detecting marker genes among many subtypes

COT detects marker genes across subtypes using cosine similarity in a one-sample test, applicable to multi-omics data.

Integrated Identification of Disease Specific Pathways Using Multi-omics data

This paper proposes two computational methods to integrate multi-omics data and identify disease-specific pathways, demonstrating their effectiveness on muscular dystrophy data.

Unsupervised deconvolution of molecular heterogeneity uncovers novel signatures and glia-neuron ratio

The paper investigates the glia-neuron ratio in the brain using unsupervised deconvolution methods on single-cell data from human brains.

Proteomic Architecture of Human Coronary and Aortic Atherosclerosis

The paper analyzes the proteomic architecture of human coronary and aortic atherosclerosis using mass spectrometry data from 200 specimens, identifying key protein networks and regulatory features associated with early disease.