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Evolutionary Approach for Relative Gene Expression Algorithms
Joint Authors
Czajkowski, Marcin
Kretowski, Marek
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-10
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
A Relative Expression Analysis (RXA) uses ordering relationships in a small collection of genes and is successfully applied to classiffication using microarray data.
As checking all possible subsets of genes is computationally infeasible, the RXA algorithms require feature selection and multiple restrictive assumptions.
Our main contribution is a specialized evolutionary algorithm (EA) for top-scoring pairs called EvoTSP which allows finding more advanced gene relations.
We managed to unify the major variants of relative expression algorithms through EA and introduce weights to the top-scoring pairs.
Experimental validation of EvoTSP on public available microarray datasets showed that the proposed solution significantly outperforms in terms of accuracy other relative expression algorithms and allows exploring much larger solution space.
American Psychological Association (APA)
Czajkowski, Marcin& Kretowski, Marek. 2014. Evolutionary Approach for Relative Gene Expression Algorithms. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-1050250
Modern Language Association (MLA)
Czajkowski, Marcin& Kretowski, Marek. Evolutionary Approach for Relative Gene Expression Algorithms. The Scientific World Journal No. 2014 (2014), pp.1-7.
https://search.emarefa.net/detail/BIM-1050250
American Medical Association (AMA)
Czajkowski, Marcin& Kretowski, Marek. Evolutionary Approach for Relative Gene Expression Algorithms. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-1050250
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1050250