Random Forest in Clinical Metabolomics for Phenotypic Discrimination and Biomarker Selection

Metabolomic data analysis becomes increasingly challenging when dealing with clinical samples with diverse demographic and genetic backgrounds and various pathological conditions or treatments. Although many classification tools, such as projection to latent structures (PLS), support vector machine...

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Dades bibliogràfiques
Autors principals: Chen, Tianlu, Cao, Yu, Zhang, Yinan, Liu, Jiajian, Bao, Yuqian, Wang, Congrong, Jia, Weiping, Zhao, Aihua
Format: Artigo
Idioma:Inglês
Publicat: Hindawi Publishing Corporation 2013
Matèries:
Research Article
Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC3594909/
https://ncbi.nlm.nih.gov/pubmed/23573122
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2013/298183
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