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...

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Detalles Bibliográficos
Autores principales: Tuikkala, Johannes, Elo, Laura L, Nevalainen, Olli S, Aittokallio, Tero
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Research Article
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

Internet

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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