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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.)

A framework for analyzing the relationship between gene expression and morphological, topological, and dynamical patterns in neuronal networks

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Author(s):
de Arruda, Henrique Ferraz [1] ; Comin, Cesar Henrique [2] ; Miazaki, Mauro [3] ; Viana, Matheus Palhares [2] ; Costa, Luciano da Fontoura [2]
Total Authors: 5
Affiliation:
[1] Univ Sao Paulo, Inst Math & Comp Sci Sao Carlos, BR-13560970 Sao Carlos, SP - Brazil
[2] Univ Sao Paulo, Inst Phys Sao Carlos, BR-13560970 Sao Carlos, SP - Brazil
[3] Midwestern State Univ, Dept Comp Sci, Guarapuava, PR - Brazil
Total Affiliations: 3
Document type: Journal article
Source: JOURNAL OF NEUROSCIENCE METHODS; v. 245, p. 1-14, APR 30 2015.
Web of Science Citations: 3
Abstract

Background: A key point in developmental biology is to understand how gene expression influences the morphological and dynamical patterns that are observed in living beings. New method: In this work we propose a methodology capable of addressing this problem that is based on estimating the mutual information and Pearson correlation between the intensity of gene expression and measurements of several morphological properties of the cells. A similar approach is applied in order to identify effects of gene expression over the system dynamics. Neuronal networks were artificially grown over a lattice by considering a reference model used to generate artificial neurons. The input parameters of the artificial neurons were determined according to two distinct patterns of gene expression and the dynamical response was assessed by considering the integrate-and-fire model. Results: As far as single gene dependence is concerned, we found that the interaction between the gene expression and the network topology, as well as between the former and the dynamics response, is strongly affected by the gene expression pattern. In addition, we observed a high correlation between the gene expression and some topological measurements of the neuronal network for particular patterns of gene expression. Comparison with existing methods: To our best understanding, there are no similar analyses to compare with. Conclusions: A proper understanding of gene expression influence requires jointly studying the morphology, topology, and dynamics of neurons. The proposed framework represents a first step towards predicting gene expression patterns from morphology and connectivity. (C) 2015 Published by Elsevier B.V. (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: 11/50761-2 - Models and methods of e-Science for life and agricultural sciences
Grantee:Roberto Marcondes Cesar Junior
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 11/22639-8 - Unveiling the relationship between structure and dynamics on modular networks
Grantee:Cesar Henrique Comin
Support Opportunities: Scholarships in Brazil - Doctorate