Display Settings:

Format

Send to:

Choose Destination
See comment in PubMed Commons below
PLoS Comput Biol. 2007 Oct;3(10):2032-42.

Construction, visualisation, and clustering of transcription networks from microarray expression data.

Author information

  • 1Division of Pathway Medicine, University of Edinburgh Medical School, Edinburgh, United Kingdom. tfreeman@staffmail.ed.ac.uk

Abstract

Network analysis transcends conventional pairwise approaches to data analysis as the context of components in a network graph can be taken into account. Such approaches are increasingly being applied to genomics data, where functional linkages are used to connect genes or proteins. However, while microarray gene expression datasets are now abundant and of high quality, few approaches have been developed for analysis of such data in a network context. We present a novel approach for 3-D visualisation and analysis of transcriptional networks generated from microarray data. These networks consist of nodes representing transcripts connected by virtue of their expression profile similarity across multiple conditions. Analysing genome-wide gene transcription across 61 mouse tissues, we describe the unusual topography of the large and highly structured networks produced, and demonstrate how they can be used to visualise, cluster, and mine large datasets. This approach is fast, intuitive, and versatile, and allows the identification of biological relationships that may be missed by conventional analysis techniques. This work has been implemented in a freely available open-source application named BioLayout Express(3D).

PMID:
17967053
[PubMed - indexed for MEDLINE]
PMCID:
PMC2041979
Free PMC Article

Images from this publication.See all images (4)Free text

Figure 1
Figure 2
Figure 3
Figure 4
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Icon for Public Library of Science Icon for PubMed Central
    Loading ...
    Write to the Help Desk