The Candidate Gene Study for Alzheimer's Disease Application of Data Mining on Microarray Analysis / 資料採礦技術應用於微陣列資料分析以篩選阿茲海默症候選基因之研究

碩士 / 輔仁大學 / 應用統計學研究所 / 97 / According to the trend of population aging, medical research of old age diseases receive much attention in recent years, Alzheimer's disease is the most serious senile dementia, there are a lot of medical researches trying to find significant genes associated with Alzheimer's disease, but still unable to effectively prevent and cure Alzheimer's disease. So, the study tries to find more genes which could induce or regulate the disease, and provides the candidate gene list for the future experiments.
This study uses the GSE1297 microarray data provided by NCBI database. First, theis study analyzes of differences between four groups, there are 1,681 genes which significant. Second, this study uses MMSE (Mini-Mental State Examination) index and NFT (NeuroFibrillary Tangle) index to classify the significant genes into four types. Third, this study using Data Mining tools-CART Decision Tree to select the candidate genes, the results are remaining 64 genes; then use the GSE5281 microarray data for correction, the results eliminate one genes, 63 genes are finally selected. Finally, the pathways cluster analysis or GO terms of candidate associated genes are integrated to recover the mechanism of AD genes. This study may provide new insights into the research on progression of AD.

Identiferoai:union.ndltd.org:TW/097FJU00506009
Date January 2009
CreatorsHsu, Yen-Pin, 許晏賓
ContributorsShia, Ben-Chang, 謝邦昌
Source SetsNational Digital Library of Theses and Dissertations in Taiwan
Languagezh-TW
Detected LanguageEnglish
Type學位論文 ; thesis
Format274

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