research-article

Mask functions for the symbolic modeling of epistasis using genetic programming

Authors:

Ryan J. Urbanowicz,

Jason H. MooreAuthors Info & Claims

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

Pages 339 - 346

https://doi.org/10.1145/1389095.1389154

Published: 12 July 2008 Publication History

Abstract

The study of common, complex multifactorial diseases in genetic epidemiology is complicated by nonlinearity in the genotype-to-phenotype mapping relationship that is due, in part, to epistasis or gene-gene interactions. Symobolic discriminant analysis (SDA) is a flexible modeling approach which uses genetic programming (GP) to evolve an optimal predictive model using a predefined collection of mathematical functions, constants, and attributes. This has been shown to be an effective strategy for modeling epistasis. In the present study, we introduce the genetic .mask. as a novel building block which exploits expert knowledge in the form of a pre-constructed relationship between two attributes. The goal of this study was to determine whether the availability of.mask.building blocks improves SDA performance. The results of this study support the idea that pre-processing data improves GP performance.

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Cited By

Romano JMei LSenn JMoore JMortensen H(2023)Exploring genetic influences on adverse outcome pathways using heuristic simulation and graph data scienceComputational Toxicology10.1016/j.comtox.2023.10026125(100261)Online publication date: Feb-2023
https://doi.org/10.1016/j.comtox.2023.100261
Colins AGerdtzen ZNuñez MSalgado J(2017)Mathematical Modeling of Intestinal Iron Absorption Using Genetic ProgrammingPLOS ONE10.1371/journal.pone.016960112:1(e0169601)Online publication date: 10-Jan-2017
https://doi.org/10.1371/journal.pone.0169601

Index Terms

Mask functions for the symbolic modeling of epistasis using genetic programming
1. Applied computing
  1. Life and medical sciences

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cover image ACM Conferences

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

Copyright © 2008 ACM.

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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Publication History

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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Cited By

Romano JMei LSenn JMoore JMortensen H(2023)Exploring genetic influences on adverse outcome pathways using heuristic simulation and graph data scienceComputational Toxicology10.1016/j.comtox.2023.10026125(100261)Online publication date: Feb-2023
https://doi.org/10.1016/j.comtox.2023.100261
Colins AGerdtzen ZNuñez MSalgado J(2017)Mathematical Modeling of Intestinal Iron Absorption Using Genetic ProgrammingPLOS ONE10.1371/journal.pone.016960112:1(e0169601)Online publication date: 10-Jan-2017
https://doi.org/10.1371/journal.pone.0169601

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