Improving missing value imputation of microarray data by using spot quality weights
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* Corresponding author: Peter Johansson peter@thep.lu.se
BMC Bioinformatics 2006, 7:306 doi:10.1186/1471-2105-7-306
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Short Report
Advanced spot quality analysis in two-colour microarray experiments Mikalai Yatskou, Eugene Novikov, Guillaume Vetter, Arnaud Muller, Emmanuel Barillot, Laurent Vallar, Evelyne Friederich BMC Research Notes 2008, 1:80 (17 September 2008) This article is part of a collection on Microarray normalization... |
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Missing value imputation for microarray gene expression data using histone acetylation information Qian Xiang, Xianhua Dai, Yangyang Deng, Caisheng He, Jiang Wang, Jihua Feng, Zhiming Dai BMC Bioinformatics 2008, 9:252 (29 May 2008) |
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Accounting for one-channel depletion improves missing value imputation in 2-dye microarray data Cecilia Ritz, Patrik Edén BMC Genomics 2008, 9:25 (19 January 2008) |
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Guy N Brock, John R Shaffer, Richard E Blakesley, Meredith J Lotz, George C Tseng BMC Bioinformatics 2008, 9:12 (10 January 2008) The best way to impute missing values in microarray data depends on the complexity of the data, and an entropy-based and a simulation-based scheme both allow researchers to select the right approach for their experimental results.
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Research
Robust imputation method for missing values in microarray data Dankyu Yoon, Eun-Kyung Lee, Taesung Park BMC Bioinformatics 2007, 8(Suppl 2):S6 (3 May 2007) |