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  2. Gene co-expression network - Wikipedia

    en.wikipedia.org/wiki/Gene_co-expression_network

    A gene co-expression network constructed from a microarray dataset containing gene expression profiles of 7221 genes for 18 gastric cancer patients A gene co-expression network (GCN) is an undirected graph , where each node corresponds to a gene , and a pair of nodes is connected with an edge if there is a significant co-expression relationship ...

  3. Weighted correlation network analysis - Wikipedia

    en.wikipedia.org/wiki/Weighted_correlation...

    Weighted correlation network analysis, also known as weighted gene co-expression network analysis (WGCNA), is a widely used data mining method especially for studying biological networks based on pairwise correlations between variables.

  4. Biological network inference - Wikipedia

    en.wikipedia.org/wiki/Biological_network_inference

    A gene co-expression network is an undirected graph, where each node corresponds to a gene, and a pair of nodes is connected with an edge if there is a significant co-expression relationship between them.

  5. Biological network - Wikipedia

    en.wikipedia.org/wiki/Biological_network

    Gene co-expression networks can be perceived as association networks between variables that measure transcript abundances. These networks have been used to provide a system biologic analysis of DNA microarray data, RNA-seq data, miRNA data, etc. weighted gene co-expression network analysis is extensively used to identify co-expression modules ...

  6. Weighted network - Wikipedia

    en.wikipedia.org/wiki/Weighted_network

    For example, weighted gene co-expression network analysis (WGCNA) is often used for constructing a weighted network among genes (or gene products) based on gene expression (e.g. microarray) data. [9] More generally, weighted correlation networks can be defined by soft-thresholding the pairwise correlations among variables (e.g. gene measurements).

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  8. RNA-Seq - Wikipedia

    en.wikipedia.org/wiki/RNA-Seq

    [131] [132] Weighted gene co-expression network analysis has been successfully used to identify co-expression modules and intramodular hub genes based on RNA seq data. Co-expression modules may correspond to cell types or pathways. Highly connected intramodular hubs can be interpreted as representatives of their respective module.

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