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Gene Selection is very important problem in the classification of serious diseases in clinical information systems. A limitation of these gene selection methods is that they may result in gene sets with some redundancy and yield an unnecessary large number of candidate genes for classification analysis. In the current work, a hybrid approach is presented in order to classify diseases, such as colon...
This paper addresses an important and vital problem within the general area of disease recognition, namely identifying disease biomarker genes. Given the complexity of this domain, the basic idea tacked in this paper is employing multiple agents to handle this problem. Though the developed methodology is general enough to be applied to any other domain, we concentrate on identifying cancer biomarkers...
This paper is aimed to predict Parkinson disease (PD) genes from multiplex Three-Dimensional brain gene expression mapping. First, we select the available data from the original datasets and use log ratio as the object that we would analysis. Second, correlation coefficient calculated provides information on the correlation between genes based on gene expression levels. Later, classification and hierarchical...
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