Missing-values imputation algorithms for microarray gene expression data

Missing-values imputation algorithms for microarray gene expression data

In gene expression studies, missing values are a common problem with important consequences for the interpretation of the final data (Satija et al., Nat Biotechnol 33(5):495, 2015). Numerous bioinformatics examination tools are used for cancer prediction, including the data set matrix (Bailey et al....

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Bibliografische gegevens
Hoofdauteurs:	Moorthy, Kohbalan, Jaber, Aws Naser, Mohd Arfian, Ismail, Ernawan, Ferda, Mohd Saberi, Mohamad, Safaai, Deris
Andere auteurs:	Bolón-Canedo, Verónica
Formaat:	Hoofdstuk
Taal:	English English English
Gepubliceerd in:	Humana Press 2019
Onderwerpen:	Q Science (General) R Medicine (General) T Technology (General)
Online toegang:	http://umpir.ump.edu.my/id/eprint/25080/1/978-1-4939-9442-7_12 http://umpir.ump.edu.my/id/eprint/25080/2/66.Missing-Values%20Imputation%20Algorithms%20for%20Microarray%20Gene%20Expression%20Data.pdf http://umpir.ump.edu.my/id/eprint/25080/3/66.1%20Missing-values%20imputation%20algorithms%20for%20microarray%20gene%20expression%20data.pdf

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