Comparison of neural network optimization approaches for studies of human genetics

Alison A. Motsinger, Scott M. Dudek, Lance W. Hahn, Marylyn D. Ritchie

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

25 Scopus citations

Abstract

A major goal of human genetics is the identification of susceptibility genes associated with common, complex diseases. The preponderance of gene-gene and gene-environment interactions comprising the genetic architecture of common diseases presents a difficult challenge. To address this, novel computational approaches have been applied to studies of human disease. These novel approaches seek to capture the complexity inherent in common diseases. Previously, we developed a genetic programming neural network (GPNN) to optimize network architecture for the detection of disease susceptibility genes in association studies. While GPNN was a successful endeavor, we wanted to address the limitations in its flexibility and ease of development. To this end, we developed a grammatical evolution neural network (GENN) approach that accounts for the drawbacks of GPNN. In this study we show that this new method has high power to detect gene-gene interactions in simulated data. We also compare the performance of GENN to GPNN, a traditional back-propagation neural network (BPNN) and a random search algorithm. GENN outperforms both BPNN and the random search, and performs at least as well as GPNN. This study demonstrates the utility of using GE to evolve NN in studies of complex human disease.

Original languageEnglish (US)
Title of host publicationApplications of Evolutionary Computing - EvoWorkshops 2006
Subtitle of host publicationEvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, and EvoSTOC, Proceedings
Pages103-114
Number of pages12
DOIs
StatePublished - Jul 14 2006
EventEvoWorkshops 2006: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, and EvoSTOC - Budapest, Hungary
Duration: Apr 10 2006Apr 12 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3907 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherEvoWorkshops 2006: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, and EvoSTOC
CountryHungary
CityBudapest
Period4/10/064/12/06

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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