Biological systems respond to perturbations through the rewiring of molecular interactions,
organised in gene regulatory networks (GRNs). Among these, the increasingly high …

Differential co-expression network analyses have recently become an important step in the
investigation of cellular differentiation and dysfunctional gene-regulation in cell and tissue …

Differential gene expression profiling studies have lead to the identification of several
disease biomarkers. However, the oncogenic alterations in coding regions can modify the …

Background Elucidation of regulatory networks, including identification of regulatory
mechanisms specific to a given biological context, is a key aim in systems biology. This has …

Gene co-expression networks can be used to associate genes of unknown function with
biological processes, to prioritize candidate disease genes or to discern transcriptional …

The study of co-expression programs in the context of cancer can help to elucidate the
genetic mechanisms that are altered and lead to the disease. The identification of gene co …

The complexity of cancer has always been a huge issue in understanding the source of this
disease. However, by appreciating its complexity, we can shed some light on crucial gene …

Motivation Differential coexpression—the alteration of gene coexpression patterns observed
in different biological conditions—has been proposed to be a mechanism for revealing …

Co-expression analysis has been employed to predict gene function, identify functional
modules, and determine tumor subtypes. Previous co-expression analysis was mainly …

Analysis of gene sets can implicate activity in signaling pathways that is responsible for
cancer initiation and progression, but is not discernible from the analysis of individual genes …