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Lecture Notes in Computer Science
Missing value imputation for microarray data is important for gene expression analysis algorithms, such as clustering, classification and network design. A number of algorithms have been proposed to solve this problem, but most of them are only limited in linear analysis methods, such as including the estimation in the linear combination of other no-missing-value genes. It may result from the fact that microarray data often comprises of huge size of genes with only a small number ofdoi:10.1007/978-3-642-24955-6_28 fatcat:njblxgf37bhg5kyfctzhixg2eu