DTW-GO Based Microarray Time Series Data Analysis for Gene-Gene Regulation Prediction

Microarray technology provides an opportunity for scientists to analyze thousands of gene expression profiles simultaneously. Due to the widely use of microarray technology, several research issues are discussed and analyzed such as missing value imputation or gene-gene regulation prediction. Microarray gene expression data often contain multiple missing expression values due to many reasons. Effective methods for missing value imputation in gene expression data are needed since many algorithms for gene analysis require a complete matrix of gene array values. In addition, selecting informative genes from microarray gene expression data is essential while performing data analysis on the large amount of data. To fit this need, a number of methods were proposed from various points of view. However, most existing methods have their limitations and disadvantages.

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