Pathway-based expression profile for breast cancer diagnoses. (Abstract/Comunicazione in atti di convegno)

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Label
  • Pathway-based expression profile for breast cancer diagnoses. (Abstract/Comunicazione in atti di convegno) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1109/EMBC.2014.6943799 (literal)
Alternative label
  • Cava C, Bertoli G, Castiglioni I. (2014)
    Pathway-based expression profile for breast cancer diagnoses.
    in Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE, Chicago, IL, 26-30 Agosto 2014
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Cava C, Bertoli G, Castiglioni I. (literal)
Pagina inizio
  • 1151 (literal)
Pagina fine
  • 1154 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 2014 (literal)
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Note
  • Abstract (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • CNR-IBFM, Segrate (MI) (literal)
Titolo
  • Pathway-based expression profile for breast cancer diagnoses. (literal)
Abstract
  • Microarray experiments have made possible to identify breast cancer marker gene signatures. However, gene expression-based signatures present limitations because they do not consider metabolic role of the genes and are affected by genetic heterogeneity across patient cohorts. Considering the activity of entire pathways rather than the expression levels of individual genes can be a way to exceed these limits. We evaluated and compared five methods of pathway-level aggregation of gene expression data. Our results confirmed the important role of pathway expression profile in breast cancer diagnostic classification (accuracy >90%). However, although assessed on a limited number of samples and datasets, this study shows that using dissimilarity representation among patients does not improve the classification of pathway-based expression profiles. (literal)
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