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Estimation of Relevant Variables on High-Dimensional Biological Patterns Using Iterated Weighted Kernel Functions
BACKGROUND: The analysis of complex proteomic and genomic profiles involves the identification of significant markers within a set of hundreds or even thousands of variables that represent a high-dimensional problem space. The occurrence of noise, redundancy or combinatorial interactions in the prof...
Tallennettuna:
| Päätekijät: | , , , , |
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| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
Public Library of Science
2008
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2396875/ https://ncbi.nlm.nih.gov/pubmed/18509521 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0001806 |
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