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Bioinformatics Advance Access published online on August 16, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti625
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oupjournals.org
Received May 18, 2005
Revised July 22, 2005
Accepted August 10, 2005

Article

Complex networks approach to gene expression driven phenotype imaging

L. Diambra 1 and L. da F. Costa 1*

1 Institute of Physics at São Carlos, University of São Paulo Caixa Postal: 369, CEP: 13560-970, São Carlos SP, Brazil

* To whom correspondence should be addressed.
L. da F. Costa, E-mail: luciano{at}if.sc.usp.br


  Abstract

Motivation: The need to visualize and quantify gene expression spatial patterns. Because of their generality for representation of interaction among several elements, complex networks are used to measure the spatial interactions and adjacencies defined by the gene expression patterns.

Results: Enhanced visualization of spatial interactions between elements where genes are expressed, allowing the identification of structures which would go unnoticed by using conventional imaging. The quantification of the expression intensity in terms of the node degree and clustering coefficient allows the identification of different types of interactions, yielding insights about cell signaling and differentiation and providing the basis for comparison and discrimination of the patterns along the developmental stages.

Availability: Supplementary material including visualizations as well as the basic routines for translating gene expression images into complex networks and obtaining node degree and clustering coefficient measurements, are provided.


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