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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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| Huvudupphovsmän: | , , |
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| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
BioMed Central
2009
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| Ämnen: | |
| Länkar: | 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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