A Genetic Classifier Account for the Regulation of Expression

Tsvi Achler () and Eyal Amir ()
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Tsvi Achler: University of Illinois Urbana-Champaign
Eyal Amir: University of Illinois Urbana-Champaign

Chapter Chapter 7 in Computational Neuroscience, 2010, pp 113-123 from Springer

Abstract: Abstract This work is motivated by our model of neuroscience processing which incorporates large numbers of reentrant top-down feedback regulation connections. Such regulation is fundamental and can be found throughout biology. The purpose of this chapter is to broaden this model's application. Genes perform important life functions, responsible for virtually every organic molecule that organisms produce. The genes must closely regulate the amount of their products, because too little or too much production may be deleterious for the organism. Furthermore, they must respond efficiently and in unison to the environments that the organism faces. Networks that are closely regulated can behave as robust classifiers which can recognize and respond to their environment. Using simple examples we demonstrate that such networks perform dynamic classification, determining the most efficient set of genes needed to replace consumed products.

Keywords: Consumption Pattern; Control Gene Expression; Product Consumption; Deleterious Gene; Communal Equilibrium (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-0-387-88630-5_7

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DOI: 10.1007/978-0-387-88630-5_7

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