Alzheimer disease is one form of dementia in old age. Alzheimer disease, the incurable disease, which is usually in the seventh decade of human life, shows its symptoms. The disease may be present for years without clinical symptoms. The current study identified the genes with altered expression in patients with Alzheimer disease. The important sequence of each gene in Alzheimer disease was found and introduced as a biomarker of this disease. The present study used microarray libraries related to Alzheimer disease. Finally, the data were weighted using 10 data mining methods, including methods such as support vector machine (SVM), deviation, information gain ratio and the Gini coefficient. Sequences with least two algorithm weights above 0.5 were selected as the most important sequences. Then, a neural network algorithm (neural net, auto multilayer perceptron and perceptron) was run on 11 data bases from the weighted perceptron algorithm, resulting in a careful 97% best performance.

Background: Alzheimer's disease is a form of dementia in old age. Alzheimer's disease is an incurable disease, usually shows its symptoms in the seventh decade of human life. This disease can exist in an individual for years without visible symptoms. The causes of this disease is still unknown although many studies have been done on this disease. Alzheimer's disease appears in an old individual based on genetic and accidental factors. Objectives: According to the importance of Alzheimer's disease and lack of a definite treatment for this disease, we decided to identify the effecting genes on this disease by using Micro-array technology. Methods: In this analytical study, Microarray technology was used to identify genes with over and down expression in patients diagnosed with Alzheimer's disease and finally, we introduced up-and down-regulated genes by using Bayes T test. Results: XIST gene, with 8.68652 over expression showed the highest level of over-expression while COL5A2 had 4.561804 downexpression which showed the most changes. Conclusions: Findings of this study, validate the previous assumptions and the only difference is in the expression level of genes which is normal due to differences in the sample.

No abstract