Partial least squares discriminant analysis (PLS-DA) provides a sound statistical basis for the selection of a limited number of gene transcripts most effective in discriminating different lung tumoral histotypes. The potentialities of the PLS-DA approach are pointed out by its ability to identify genes which, according to current knowledge, are considered molecular markers for colon cancer diagnostics and classification. Indeed application of PLS-DA to in vivo data allowed identification of a set of genes able to discriminate primary lung tumours from colon metastases. (c) 2005 Elsevier Ltd. All rights reserved.

Genome-based identification of diagnostic molecular markers for human lung carcinomas by PLS-DA RID H-2208-2011

MUSUMARRA, Giuseppe;CONDORELLI, Daniele Filippo;FORTUNA, COSIMO GIANLUCA;SCIRE', Salvatore
2005-01-01

Abstract

Partial least squares discriminant analysis (PLS-DA) provides a sound statistical basis for the selection of a limited number of gene transcripts most effective in discriminating different lung tumoral histotypes. The potentialities of the PLS-DA approach are pointed out by its ability to identify genes which, according to current knowledge, are considered molecular markers for colon cancer diagnostics and classification. Indeed application of PLS-DA to in vivo data allowed identification of a set of genes able to discriminate primary lung tumours from colon metastases. (c) 2005 Elsevier Ltd. All rights reserved.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/43261
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