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Applying gene regulatory network logic to the evolution of social behavior
Author(s) -
Nicole M. Baran,
Patrick T. McGrath,
J. Todd Streelman
Publication year - 2017
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.1610621114
Subject(s) - encode , gene regulatory network , analogy , perspective (graphical) , function (biology) , artificial neural network , computer science , brain function , neuroscience , genomics , artificial intelligence , cognitive science , biology , gene , psychology , genome , genetics , gene expression , linguistics , philosophy
Animal behavior is ultimately the product of gene regulatory networks (GRNs) for brain development and neural networks for brain function. The GRN approach has advanced the fields of genomics and development, and we identify organizational similarities between networks of genes that build the brain and networks of neurons that encode brain function. In this perspective, we engage the analogy between developmental networks and neural networks, exploring the advantages of using GRN logic to study behavior. Applying the GRN approach to the brain and behavior provides a quantitative and manipulative framework for discovery. We illustrate features of this framework using the example of social behavior and the neural circuitry of aggression.

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