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Bioinformatics

Volume 453 of the series Methods in Molecular Biology™ pp 379-392

Genetic Signatures for a Rodent Model of Parkinson's Disease Using Combinatorial Optimization Methods

  • Mou'ath HouraniAffiliated withNewcastle Bioinformatics Initiative, School of Electrical Engineering and Computer Science, The University of Newcastle
  • , Regina BerrettaAffiliated withCentre of Bioinformatics, Biomarker Discovery and Information-Based Medicine, The University of Newcastle
  • , Alexandre MendesAffiliated withCentre of Bioinformatics, Biomarker Discovery and Information-Based Medicine, The University of Newcastle
  • , Pablo MoscatoAffiliated withARC Centre of Excellence in Bioinformatics, and Centre of Bioinformatics, Biomarker Discovery and Information-Based Medicine, The University of Newcastle

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Abstract

This chapter illustrates the use of the combinatorial optimization models presented in Chapter 19 for the Feature Set selection and Gene Ordering problems to find genetic signatures for diseases using micro-array data. We demonstrate the quality of this approach by using a microarray dataset from a mouse model of Parkinson's disease. The results are accompanied by a description of the currently known molecular functions and biological processes of the genes in the signatures.

Key words:

Parkinson's disease combinatorial optimization gene selection microarray data analysis feature selection gene ordering