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Using expert knowledge in initialization for genome-wide analysis of epistasis using genetic programming

Authors:

Casey S. Greene,

Bill C. White,

Jason H. MooreAuthors Info & Claims

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

Pages 351 - 352

https://doi.org/10.1145/1389095.1389158

Published: 12 July 2008 Publication History

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Abstract

In human genetics it is now possible to measure large numbers of DNA sequence variations across the human genome. Given current knowledge about biological networks and disease processes it seems likely that disease risk can best be modeled by interactions between biological components, which may be examined as interacting DNA sequence variations. The machine learning challenge is to e.ectively explore interactions in these datasets to identify combinations of variations which are predictive of common human diseases. Genetic programming is a promising approach to this problem. The goal of this study is to examine the role that an expert knowledge aware initializer can play in the framework of genetic programming. We show that this expert knowledge aware initializer outperforms both a random initializer and an enumerative initializer.

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Greene CMoore J(2012)Solving Complex Problems in Human Genetics Using Nature-Inspired Algorithms Requires Strategies which Exploit Domain-Specific KnowledgeComputer Engineering10.4018/978-1-61350-456-7.ch804(1867-1881)Online publication date: 2012
https://doi.org/10.4018/978-1-61350-456-7.ch804
Schmidt MLipson HRothlauf F(2009)Incorporating expert knowledge in evolutionary searchProceedings of the 11th Annual conference on Genetic and evolutionary computation10.1145/1569901.1570048(1091-1098)Online publication date: 8-Jul-2009
https://dl.acm.org/doi/10.1145/1569901.1570048
Greene CMoore J(2008)Solving complex problems in human genetics using GPACM SIGEVOlution10.1145/1527063.15270643:2(2-8)Online publication date: 1-Jul-2008
https://dl.acm.org/doi/10.1145/1527063.1527064

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Using expert knowledge in initialization for genome-wide analysis of epistasis using genetic programming
1. Applied computing
  1. Life and medical sciences

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Published In

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

July 2008

1814 pages

ISBN:9781605581309

DOI:10.1145/1389095

Conference Chair:
Conor Ryan
University of Limerick, Ireland
,
Editor:
Maarten Keijzer
Chordiant Software International B.V., The Netherlands

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 12 July 2008

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GECCO08: Genetic and Evolutionary Computation Conference

July 12 - 16, 2008

GA, Atlanta, USA

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Greene CMoore J(2012)Solving Complex Problems in Human Genetics Using Nature-Inspired Algorithms Requires Strategies which Exploit Domain-Specific KnowledgeComputer Engineering10.4018/978-1-61350-456-7.ch804(1867-1881)Online publication date: 2012
https://doi.org/10.4018/978-1-61350-456-7.ch804
Schmidt MLipson HRothlauf F(2009)Incorporating expert knowledge in evolutionary searchProceedings of the 11th Annual conference on Genetic and evolutionary computation10.1145/1569901.1570048(1091-1098)Online publication date: 8-Jul-2009
https://dl.acm.org/doi/10.1145/1569901.1570048
Greene CMoore J(2008)Solving complex problems in human genetics using GPACM SIGEVOlution10.1145/1527063.15270643:2(2-8)Online publication date: 1-Jul-2008
https://dl.acm.org/doi/10.1145/1527063.1527064

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Exploiting Expert Knowledge in Genetic Programming for Genome-Wide Genetic Analysis

Genome-wide analysis of intergenic regions of mycobacterium tuberculosis H37Rv using affymetrix genechips

Genome-wide functional element detection using pairwise statistical alignment outperforms multiple genome footprinting techniques

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