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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...
| Autores principales: | , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2009
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795972/ https://www.ncbi.nlm.nih.gov/pubmed/20018065 |