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BMCBI
2006
103views more  BMCBI 2006»
11 years 5 months ago
Improving missing value imputation of microarray data by using spot quality weights
Background: Microarray technology has become popular for gene expression profiling, and many analysis tools have been developed for data interpretation. Most of these tools requir...
Peter Johansson, Jari Häkkinen
BMCBI
2008
190views more  BMCBI 2008»
11 years 5 months ago
Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes
Background: Gene expression data frequently contain missing values, however, most downstream analyses for microarray experiments require complete data. In the literature many meth...
Guy N. Brock, John R. Shaffer, Richard E. Blakesle...
BMCBI
2008
104views more  BMCBI 2008»
11 years 5 months ago
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 i...
Johannes Tuikkala, Laura Elo, Olli Nevalainen, Ter...
WCE
2007
11 years 6 months ago
A Dynamic Method for the Evaluation and Comparison of Imputation Techniques
— Imputation of missing data is important in many areas, such as reducing non-response bias in surveys and maintaining medical documentation. Estimating the uncertainty inherent ...
Norman Solomon, Giles Oatley, Kenneth McGarry
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