Année de publication
2014
Type
Conférence
Description
IAPR International Conference on Pattern Recognition in Bioinformatics, Pages 48-59, Springer
Résumé
Microarray represents a recent multidisciplinary technology. It measures the expression levels of several genes under different biological conditions, which allows to generate multiple data. These data can be analyzed through biclustering method to determinate groups of genes presenting a similar behavior under specific groups of conditions.
This paper proposes a new evolutionary algorithm based on a new crossover method, dedicated to the biclustering of gene expression data. This proposed crossover method ensures the creation of new biclusters with better quality. To evaluate its performance, an experimental study was done on real microarray datasets. These experimentations show that our algorithm extracts high quality biclusters with highly correlated genes that are particularly involved in specific ontology structure.
BibTeX
@InProceedings{10.1007/978-3-319-09192-1_5,
author="Ma{\^a}touk, Ons
and Ayadi, Wassim
and Bouziri, Hend
and Duval, Beatrice",
editor="Comin, Matteo
and K{\"a}ll, Lukas
and Marchiori, Elena
and Ngom, Alioune
and Rajapakse, Jagath",
title="Evolutionary Algorithm Based on New Crossover for the Biclustering of Gene Expression Data",
booktitle="Pattern Recognition in Bioinformatics",
year="2014",
publisher="Springer International Publishing",
address="Cham",
pages="48--59",
isbn="978-3-319-09192-1"
}
Lien
Wassim Ayadi