Missing value imputation improves clustering and interpretation of gene expression microarray data
<p>Abstract</p> <p>Background</p> <p>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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2008-04-01
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| Series: | BMC Bioinformatics |
| Online Access: | http://www.biomedcentral.com/1471-2105/9/202 |