TJENG
Using Adaptive Neuro-Fuzzy Inference System for Classification of Microarray Gene Expression Cancer Profiles
Bulent HAZNEDAR,Mustafa Turan ARSLAN,Adem KALINLI
Keywords: Classification, microarray gene expression, statistical methods, artificial intelligence, fuzzy logic, ANFIS.
Abstract: Microarray is a technology that enables simultaneously analysis of thousands of genes in DNA structure depending on the advances in biochemistry. With this technology, it has become possible to diagnose and treat heredity diseases by analyzing thousands of gene expression levels. This study proposes an artificial intelligence method, Adaptive neuro-fuzzy inference system (ANFIS), to classify cancer gene expression profiles. The findings obtained with the proposed ANFIS approach are compared with the results of statistical methods such as Naive Bayes and Support Vector Machines. In conclusion, although the highest average classification performance achieved with ANFIS is 95.56%, the highest performance achieved with statistical methods are found to be 87.65%.
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