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Integrative Sparse Principal Component Analysis of Gene Expression Data

In the analysis of gene expression data, dimension reduction techniques have been extensively adopted. The most popular one is perhaps the PCA (principal component analysis). To generate more reliable and more interpretable results, the SPCA (sparse PCA) technique has been developed. With the “small...

Täydet tiedot

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Bibliografiset tiedot
Julkaisussa:Genet Epidemiol
Päätekijät: Liu, Mengque, Fan, Xinyan, Fang, Kuangnan, Zhang, Qingzhao, Ma, Shuangge
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: 2017
Aiheet:
Linkit:https://ncbi.nlm.nih.gov/pmc/articles/PMC5912177/
https://ncbi.nlm.nih.gov/pubmed/29114920
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/gepi.22089
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