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Missing value imputation improves clustering and interpretation of gene expression microarray data
BACKGROUND: Missing values frequently pose problems in gene expression microarray experiments as they can hinder downstream analysis of the datasets. While several missing value imputation approaches are available to the microarray users and new ones are constantly being developed, there is no gener...
Autores principales: | Tuikkala, Johannes, Elo, Laura L, Nevalainen, Olli S, Aittokallio, Tero |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2386492/ https://www.ncbi.nlm.nih.gov/pubmed/18423022 http://dx.doi.org/10.1186/1471-2105-9-202 |
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