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Modelling Amylopectin Biosynthesis with Evolved Stigmergic Building Algorithms

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Title: Modelling Amylopectin Biosynthesis with Evolved Stigmergic Building Algorithms
Author: Goren, Asena
Department: Department of Mathematics and Statistics
Program: Bioinformatics
Advisor: Ashlock, DanielTetlow, Ian
Abstract: This thesis describes the investigation of the use of evolutionary computation to evolve stigmergic building algorithms to simulate the interplay of biosynthetic enzymes that is necessary to produce the amylopectin polysaccharides that are the major component of starch. Amylopectins are large, branched, semi-crystalline glucose polymers that are synthesized by a diverse group of enzymes with different functionalities. The structure and synthesis of amylopectin is not yet fully understood. This study uses an evolutionary computational model combined with a stigmergic model of wasp behaviour to elucidate unanswered questions about amylopectin biosynthesis. The interplay of three functional groups of enzymes, synthases, branchers, and debranchers, are modelled and analysed to determine their relative activities, context sensitivities, and roles in amylopectin synthesis.
Date: 2017-04-20

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