Initialization parameter sweep in ATHENA: optimizing neural networks for detecting gene-gene interactions in the presence of small main effects

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Holzinger:2010:gecco,
  author =       "Emily Rose Holzinger and Carrie C. Buchanan and 
                 Scott M. Dudek and Eric C. Torstenson and 
                 Stephen D. Turner and Marylyn D. Ritchie",
  title =        "Initialization parameter sweep in ATHENA: optimizing
                 neural networks for detecting gene-gene interactions in
                 the presence of small main effects",
  booktitle =    "GECCO '10: Proceedings of the 12th annual conference
                 on Genetic and evolutionary computation",
  year =         "2010",
  editor =       "Juergen Branke and Martin Pelikan and Enrique Alba and 
                 Dirk V. Arnold and Josh Bongard and 
                 Anthony Brabazon and Juergen Branke and Martin V. Butz and 
                 Jeff Clune and Myra Cohen and Kalyanmoy Deb and 
                 Andries P Engelbrecht and Natalio Krasnogor and 
                 Julian F. Miller and Michael O'Neill and Kumara Sastry and 
                 Dirk Thierens and Jano {van Hemert} and Leonardo Vanneschi and 
                 Carsten Witt",
  isbn13 =       "978-1-4503-0072-8",
  pages =        "203--210",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution, Bioinformatics, computational, systems and
                 synthetic biology",
  month =        "7-11 " # jul,
  organisation = "SIGEVO",
  address =      "Portland, Oregon, USA",
  DOI =          "doi:10.1145/1830483.1830519",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "Recent advances in genotyping technology have led to
                 the generation of an enormous quantity of genetic data.
                 Traditional methods of statistical analysis have proved
                 insufficient in extracting all of the information about
                 the genetic components of common, complex human
                 diseases. A contributing factor to the problem of
                 analysis is that amongst the small main effects of each
                 single gene on disease susceptibility, there are
                 non-linear, gene-gene interactions that can be
                 difficult for traditional, parametric analyses to
                 detect. In addition, exhaustively searching all
                 multi-locus combinations has proved computationally
                 impractical. Novel strategies for analysis have been
                 developed to address these issues. The Analysis Tool
                 for Heritable and Environmental Network Associations
                 (ATHENA) is an analytical tool that incorporates
                 grammatical evolution neural networks (GENN) to detect
                 interactions among genetic factors. Initial parameters
                 define how the evolutionary process will be
                 implemented. This research addresses how different
                 parameter settings affect detection of disease models
                 involving interactions. In the current study, we
                 iterate over multiple parameter values to determine
                 which combinations appear optimal for detecting
                 interactions in simulated data for multiple genetic
                 models. Our results indicate that the factors that have
                 the greatest influence on detection are: input variable
                 encoding, population size, and parallel computation.",
  notes =        "Carrie C Buchanan's 2013 PhD
                 http://etd.library.vanderbilt.edu/available/etd-11272013-142349/
                 not GP

                 Also known as \cite{1830519} GECCO-2010 A joint meeting
                 of the nineteenth international conference on genetic
                 algorithms (ICGA-2010) and the fifteenth annual genetic
                 programming conference (GP-2010)",
}

Genetic Programming entries for Emily Rose Holzinger Carrie C Buchanan Scott M Dudek Eric C Torstenson Stephen D Turner Marylyn D Ritchie

Citations