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A scale space approach for unsupervised feature selection in mass spectra classification for ovarian cancer detection

BACKGROUND: Mass spectrometry spectra, widely used in proteomics studies as a screening tool for protein profiling and to detect discriminatory signals, are high dimensional data. A large number of local maxima (a.k.a. peaks) have to be analyzed as part of computational pipelines aimed at the realiz...

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Hlavní autoři: Ceccarelli, Michele, d'Acierno, Antonio, Facchiano, Angelo
Médium: Artigo
Jazyk:Inglês
Vydáno: BioMed Central 2009
Témata:
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC2762074/
https://ncbi.nlm.nih.gov/pubmed/19828085
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-10-S12-S9
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