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Chapter 7
A Genetic Classifier Account for the Regulation
of Expression
Tsvi Achler and Eyal Amir
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 environ-
ments that the organism faces. Networks that are closely regulated can behave as
robust classifiers which can recognize and respond to their environment. Using sim-
ple examples we demonstrate that such networks perform dynamic classification,
determining the most efficient set of genes needed to replace consumed products.
7.1 Introduction
7.1.1 Motivation
Genes working together are involved in the production and regulation of proteins
and precursors necessary to maintain life. These genetic networks must self-regulate
their expression in order to produce the correct products in practical amounts. The
