Genetic signatures for a rodent model of Parkinson's disease using combinatorial optimization methods | NOVA. The University of Newcastle's Digital Repository

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/804491

Title: Genetic signatures for a rodent model of Parkinson's disease using combinatorial optimization methods
Author/Creator: Hourani, Mou'Ath; Berretta, Regina; Mendes, Alexandre; Moscato, Pablo
Institution: The University of Newcastle. Faculty of Engineering & Built Environment, School of Electrical Engineering and Computer Science
Description: 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 microarray 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.
Relation: Bioinformatics, Volume 2 p. 379-392
Relation: Methods in Molecular Biology 453
Publisher Link: http://dx.doi.org/10.1007/978-1-60327-429-6
Date: 2008
Publisher: Humana Press
Keyword(s): Parkinson's disease; combinatorial optimization; gene selection; microarray data analysis; feature selection; gene ordering
Resource Type: book chapter
Identifier: http://hdl.handle.net/1959.13/804491
Identifier: ISBN:9781603274289

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