الفهرس 
Applications for DNA MicroarrayOnly 14 pages are availabe for public view
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Abstract
DNA microarray technology is one of the most important tools in functional genomics research. This technology is involved in a variety of biological researches, such as classifying and detecting cancer and identifying genes relevant to a certain disease or phenomena. One of the most critical techniques in microarray data analysis, called feature selection and classification, which are responsible for choosing the most valuable subset of gene expressions related to under conditioned phenomena such as cancer virus or bacterial effects and building classifiers to distinguish and predict these phenomena These valuable techniques suffer from missing data in the microarray data sets because microarray data sets can contain up to 10% of missing data and in some cases up to 90% of gene expressions have one or more missing data and feature selection and classification could not be performed in the existence of missing data. One simple solution for solving this problem is to repeat the high cost microarray experiment more than one time, which is very expensive or filling the missing data with any arbitrary values which leads to a mess in the results of the microarray data analysis techniques.