Sentence examples for modules of correlated from inspiring English sources

MMC produces modules of correlated transcripts which can be interpreted as gene networks that are often biologically-meaningful [50], [51].

Nine communities (modules) of correlated analytes were identified in the resulting network using community structure statistics [33], reflecting conservation of some metabolic modules between genotypes.

We used whole-genome transcriptional profiling to identify modules of correlated transcripts expressed in adult worker brains associated with retinue response, and found hundreds of transcriptional differences significantly associated with individual behavioral variation.

We identified five modules of correlated transcripts, ranging from 2 to 69 probe sets.

We identified 5 modules of correlated transcripts associated with TAG, ranging from 1 to 71 probe sets (see Additional file 5: Modules of correlated transcripts associated with body weight and energy metabolism traits).

We identified 13 modules of correlated transcripts associated with BW, ranging from 2 to 97 probe sets (see Additional file 5: Modules of correlated transcripts associated with body weight and energy metabolism traits).

This analytical pipeline highlights the potential applicability of an unsupervised correlation network approach, whereby functional characterization of correlated gene modules provides insight into the molecular mechanisms underlying a clinical trait of a complex pulmonary disease.

12– 16 Within a coexpression network, a module represents a group of correlated genes, based on expression profiles, which likely share genetic regulation and/or biological function.

Given our data for the control/wild type cross-species comparison, the negatively correlated modules of the human HD caudate nucleus dataset were very highly preserved in the mouse models, while the positively correlated modules were in general less highly preserved.

A weighted gene coexpression network analysis was then performed based on the microarray expression data to identify distinct coexpression modules corresponding to the clusters of correlated genes (Langfelder and Horvath 2008).

Thus, this method allows detection of correlated miRNA mRNA modules from multiple data sources by using a balanced fitness function.