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Unsupervised reduction of random noise in complex data by a row-specific, sorted principal component-guided method
BACKGROUND: Large biological data sets, such as expression profiles, benefit from reduction of random noise. Principal component (PC) analysis has been used for this purpose, but it tends to remove small features as well as random noise. RESULTS: We interpreted the PCs as a mere signal-rich coordina...
| Autores principales: | , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2008
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2607290/ https://www.ncbi.nlm.nih.gov/pubmed/19040754 http://dx.doi.org/10.1186/1471-2105-9-508 |