Gene Network Reconstruction Using a Distributed Genetic Algorithm with a Backprop Local Search

Mark Cumiskey, John Levine, Douglas Armstrong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With the first draft completion of multiple organism genome sequencing programmes the emphasis is now moving toward a functional understanding of these genes and their network interactions. Microarray technology allows for large-scale gene experimentation. Using this technology it is possible to find the expression levels of genes across different conditions. The use of a genetic algorithm with a backpropagation local searching mechanism to reconstruct gene networks was investigated. This study demonstrates that the distributed genetic algorithm approach shows promise in that the method can infer gene networks that fit test data closely. Evaluating the biological accuracy of predicted networks from currently available test data is not possible. The best that can be achieved is to produce a set of possible networks to pass to a biologist for experimental verification.
Original languageEnglish
Title of host publicationApplications of Evolutionary Computing
Subtitle of host publicationEvoWorkshops 2003: EvoBIO, EvoCOP, EvoIASP, EvoMUSART, EvoROB, and EvoSTIM Essex, UK, April 14–16, 2003 Proceedings
EditorsStefano Cagnoni, Colin Johnson, Juan Cardalda, Elena Marchiori, David Corne, Jean-Arcady Meyer, Jens Gottlieb, Martin Middendorf, Agnès Guillot, Günther Raidl, Emma Hart
PublisherSpringer Berlin Heidelberg
Pages177-181
Number of pages5
ISBN (Electronic)978-3-540-36605-8
ISBN (Print)978-3-540-00976-4
DOIs
Publication statusPublished - 2003

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin Heidelberg
Volume2611
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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