Computational, integrative, and comparative methods for the elucidation of genetic coexpression networks

  • Baldwin N
  • Chesler E
  • Kirov S
 et al. 
  • 47

    Readers

    Mendeley users who have this article in their library.
  • 28

    Citations

    Citations of this article.

Abstract

Gene expression microarray data can be used for the assembly of genetic coexpression network graphs. Using mRNA samples obtained from recombinant inbred Mus musculus strains, it is possible to integrate allelic variation with molecular and higher-order phenotypes. The depth of quantitative genetic analysis of microarray data can be vastly enhanced utilizing this mouse resource in combination with powerful computational algorithms, platforms, and data repositories. The resulting network graphs transect many levels of biological scale. This approach is illustrated with the extraction of cliques of putatively co-regulated genes and their annotation using gene ontology analysis and cis-regulatory element discovery. The causal basis for co-regulation is detected through the use of quantitative trait locus mapping.

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Authors

  • Nicole E. Baldwin

  • Elissa J. Chesler

  • Stefan Kirov

  • Michael A. Langston

  • Jay R. Snoddy

  • Robert W. Williams

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free