Gene selection based on multi-class support vector machines and genetic algorithms
Genet. mol. res. (Online)
; Genet. mol. res. (Online);4(3): 599-607, 2005.
Article
em En
| LILACS
| ID: lil-444951
Biblioteca responsável:
BR1.1
ABSTRACT
Microarrays are a new technology that allows biologists to better understand the interactions between diverse pathologic state at the gene level. However, the amount of data generated by these tools becomes problematic, even though data are supposed to be automatically analyzed (e.g., for diagnostic purposes). The issue becomes more complex when the expression data involve multiple states. We present a novel approach to the gene selection problem in multi-class gene expression-based cancer classification, which combines support vector machines and genetic algorithms. This new method is able to select small subsets and still improve the classification accuracy.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
LILACS
Assunto principal:
Seleção Genética
/
Algoritmos
/
Análise de Sequência com Séries de Oligonucleotídeos
/
Perfilação da Expressão Gênica
/
Modelos Genéticos
Tipo de estudo:
Diagnostic_studies
Limite:
Humans
Idioma:
En
Revista:
Genet. mol. res. (Online)
Assunto da revista:
BIOLOGIA MOLECULAR
/
GENETICA
Ano de publicação:
2005
Tipo de documento:
Article
País de afiliação:
Brasil
País de publicação:
Brasil