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Gene expression data classification combining hierarchical representation and efficient feature selection

Autor
Bosio, M.; Bellot, P.; Salembier, P.; Oliveras, A.
Tipus d'activitat
Article en revista
Revista
Journal of biological systems
Data de publicació
2012-12
Volum
20
Número
4
Pàgina inicial
349
Pàgina final
375
DOI
https://doi.org/10.1142/S0218339012400025 Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/18425 Obrir en finestra nova
URL
http://www.worldscientific.com/doi/pdfplus/10.1142/S0218339012400025 Obrir en finestra nova
Resum
A general framework for microarray data classification is proposed in this paper. It pro- duces precise and reliable classifiers through a two-step approach. At first, the original feature set is enhanced by a new set of features called metagenes. These new features are obtained through a hierarchical clustering process on the original data. Two different metagene generation rules have been analyzed, called Treelets clustering and Euclidean clustering. Metagenes creation is attractive for severa...
Citació
Bosio, M. [et al.]. Gene expression data classification combining hierarchical representation and efficient feature selection. "Journal of biological systems", Desembre 2012, vol. 20, núm. 4, p. 349-375.
Paraules clau
LDA, Microarray classification, Treelets, feature selection, hierarchical representation, metagenes
Grup de recerca
GPI - Grup de Processament d'Imatge i Vídeo
IDEAI-UPC Intelligent Data Science and Artificial Intelligence

Participants