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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Study of cerebral gene expression densities using Voronoi analysis

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Author(s):
Miazaki, Mauro [1] ; Costa, Luciano da F. [1, 2]
Total Authors: 2
Affiliation:
[1] Univ Sao Paulo, Inst Phys Sao Carlos, BR-13560970 Sao Carlos, SP - Brazil
[2] Natl Inst Sci & Technol Complex Syst, Niteroi, RJ - Brazil
Total Affiliations: 2
Document type: Journal article
Source: JOURNAL OF NEUROSCIENCE METHODS; v. 203, n. 1, p. 212-219, JAN 15 2012.
Web of Science Citations: 2
Abstract

As the available public cerebral gene expression image data increasingly grows, the demand for automated methods to analyze such large amount of data also increases. An important study that can be carried out on these data is related to the spatial relationship between gene expressions. Similar spatial density distribution of expression between genes may indicate they are functionally correlated, thus the identification of these similarities is useful in suggesting directions of investigation to discover gene interactions and their correlated functions. In this paper, we describe the use of a high-throughput methodology based on Voronoi diagrams to automatically analyze and search for possible local spatial density relationships between gene expression images. We tested this method using mouse brain section images from the Allen Mouse Brain Atlas public database. This methodology provided measurements able to characterize the similarity of the density distribution between gene expressions and allowed the visualization of the results through networks and Principal Component Analysis (PCA). These visualizations are useful to analyze the similarity level between gene expression patterns, as well as to compare connection patterns between region networks. Some genes were found to have the same type of function and to be near each other in the PCA visualizations. These results suggest cerebral density correlations between gene expressions that could be further explored. (C) 2011 Elsevier B.V. All rights reserved. (AU)

FAPESP's process: 07/50988-1 - Study of form, function and gene expression in neuroscience
Grantee:Mauro Miazaki
Support Opportunities: Scholarships in Brazil - Doctorate
FAPESP's process: 05/00587-5 - Mesh (graph) modeling and techniques of pattern recognition: structure, dynamics and applications
Grantee:Roberto Marcondes Cesar Junior
Support Opportunities: Research Projects - Thematic Grants