Unsupervised reduction of random noise in complex data by a row-specific, sorted principal component-guided method
<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>We interpreted...
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| Autors principals: | , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
BMC
2008-11-01
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| Col·lecció: | BMC Bioinformatics |
| Accés en línia: | http://www.biomedcentral.com/1471-2105/9/508 |
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