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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Study of cerebral gene expression densities using Voronoi analysis

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Autor(es):
Miazaki, Mauro [1] ; Costa, Luciano da F. [1, 2]
Número total de Autores: 2
Afiliação do(s) autor(es):
[1] Univ Sao Paulo, Inst Phys Sao Carlos, BR-13560970 Sao Carlos, SP - Brazil
[2] Natl Inst Sci & Technol Complex Syst, Niteroi, RJ - Brazil
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: JOURNAL OF NEUROSCIENCE METHODS; v. 203, n. 1, p. 212-219, JAN 15 2012.
Citações Web of Science: 2
Resumo

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)

Processo FAPESP: 05/00587-5 - Modelagem por redes (grafos) e técnicas de reconhecimento de padrões: estrutura, dinâmica e aplicações
Beneficiário:Roberto Marcondes Cesar Junior
Linha de fomento: Auxílio à Pesquisa - Temático
Processo FAPESP: 07/50988-1 - Estudo da forma, função e expressão gênica em neurociência
Beneficiário:Mauro Miazaki
Linha de fomento: Bolsas no Brasil - Doutorado