Multiclass classification of microarray data with repeated measurements: application to cancer
AUTOR(ES)
Yeung, Ka Yee
FONTE
BioMed Central
RESUMO
Prediction of the diagnostic category of a tissue sample from its gene-expression profile and selection of relevant genes for class prediction have important applications in cancer research. Uncorrelated shrunken centroid and error-weighted, uncorrelated shrunken centroid algorithms have been developed that are applicable to microarray data with any number of classes.
ACESSO AO ARTIGO
http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=329422Documentos Relacionados
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