Understanding diseases requires identifying the differences between healthy and affected
tissues. Gene expression data have revolutionized the study of diseases by making it …

The recent accumulation of gene expression data in the form of RNA sequencing creates
unprecedented opportunities to study gene regulation and function. Furthermore …

High-throughput measurements of gene expression and genetic marker data facilitate
systems biologic and systems genetic data analysis strategies. Gene co-expression …

Background There is evidence that genes and their protein products are organized into
functional modules according to cellular processes and pathways. Gene co-expression …

Gene regulatory networks, in which differential expression of regulator genes induce
differential expression of their target genes, underlie diverse biological processes such as …

Motivation: Standard analysis routines for microarray data aim at differentially expressed
genes. In this paper, we address the complementary problem of detecting sets of …

Gene coexpression analysis was developed to explore gene interconnection at the
expression level from a systems perspective, and differential coexpression analysis (DCEA) …

The main challenge for gaining biological insights from genetic associations is identifying
which genes and pathways explain the associations. Here we present DEPICT, an …

Background The analysis of modular gene co-expression networks is a well-established
method commonly used for discovering the systems-level functionality of genes. In addition …

Motivation: The rapid accumulation of microarray datasets provides unique opportunities to
perform systematic functional characterization of the human genome. We designed a graph …