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.File in questo prodotto:
File | Dimensione | Formato | |
---|---|---|---|
Computational-Biology-and-Chemistry 2005.pdf
solo gestori archivio
Tipologia:
Versione Editoriale (PDF)
Licenza:
NON PUBBLICO - Accesso privato/ristretto
Dimensione
474.58 kB
Formato
Adobe PDF
|
474.58 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.