Cancer Gene Detection Using Neuro Fuzzy Classification Algorithm
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Abstract
Clustering has been used extensively as a vital tool of data mining. A Neuro-Fuzzy method is proposed in this research for analyzing the gene expression data from microarray experiments. Analysis of gene expression data leads to cancer identification and classification, which will facilitate proper treatment selection and drug development. The proposed approach was tested on three benchmark cancer gene expression data sets. Experimental results show that our Neuro-Fuzzy method can be used as an efficient computational tool for microarray data analysis. The Neuro-Fuzzy classification system, which is based on a built clustering algorithm reached recognition rates than other classifiers. Gene expression data sets for liver cancer were analyzed in this research. A training and test data set for each cancer was used to analyze the quality of the genes. The researchers with a better understanding of the data.
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