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An application of Random Forests to a genome-wide association dataset: Methodological considerations & new findings

<p>Abstract</p> <p>Background</p> <p>As computational power improves, the application of more advanced machine learning techniques to the analysis of large genome-wide association (GWA) datasets becomes possible. While most traditional statistical methods can only eluci...

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Bibliografski detalji
Glavni autori: Hubbard Alan E, Goldstein Benjamin A, Cutler Adele, Barcellos Lisa F
Format: Artigo
Jezik:Inglês
Izdano: BMC 2010-06-01
Serija:BMC Genetics
Online pristup:http://www.biomedcentral.com/1471-2156/11/49
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