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Selection of important variables by statistical learning in genome-wide association analysis
Genetic analysis of complex diseases demands novel analytical methods to interpret data collected on thousands of variables by genome-wide association studies. The complexity of such analysis is multiplied when one has to consider interaction effects, be they among the genetic variations (G × G) or...
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| Main Authors: | , |
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| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
BioMed Central
2009
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| Fag: | |
| Online adgang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2795972/ https://ncbi.nlm.nih.gov/pubmed/20018065 |
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