Gene co-expression networks are increasingly used to explore the system-level functionality
of genes. The network construction is conceptually straightforward: nodes represent genes …

The merging of network theory and microarray data analysis techniques has spawned a new
field: gene coexpression network analysis. While network methods are increasingly used in …

Background Network analyses, such as of gene co-expression networks, metabolic
networks and ecological networks have become a central approach for the systems-level …

Weighted gene coexpression network analysis (WGCNA) has been applied to many
important studies since its introduction in 2005. WGCNA can be used as a data exploratory …

Background Gene co-expression networks are often constructed by computing some
measure of similarity between expression levels of gene transcripts and subsequently …

Background Correlation networks are increasingly being used in bioinformatics applications.
For example, weighted gene co-expression network analysis is a systems biology method …

Background Co-expression measures are often used to define networks among genes.
Mutual information (MI) is often used as a generalized correlation measure. It is not clear …

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

Weighted gene co-expression network analysis (WGCNA) is used to detect clusters with
highly correlated genes. Measurements of correlation most typically rely on linear …

Background To construct gene co-expression networks, it is necessary to evaluate the
correlation between different gene expression profiles. However, commonly used correlation …