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....
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Book Section |
| Language: | English English English |
| Published: |
Humana Press
2019
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/25080/ http://umpir.ump.edu.my/id/eprint/25080/ http://umpir.ump.edu.my/id/eprint/25080/ 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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http://umpir.ump.edu.my/id/eprint/25080/
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