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  • 标题:Function and Pathway Analysis of Differentially Expressed Genes in Alzheimer’s Disease Dataset Using Linear Regression Model
  • 本地全文:下载
  • 作者:Dr. R. Porkodi ; R. Savitha
  • 期刊名称:International Journal of Computer Science & Technology
  • 印刷版ISSN:2229-4333
  • 电子版ISSN:0976-8491
  • 出版年度:2015
  • 卷号:6
  • 期号:4
  • 页码:226-230
  • 语种:English
  • 出版社:Ayushmaan Technologies
  • 摘要:Alzheimer’s disease is an irreversible, progressive brain disorder that slowly destroys memory and thinking skills, and eventually the ability to carry out the simplest tasks. The aim of this study is to screen the potential pathways changed in Alzheimer’s disease and elucidate the mechanism of it. Published microarray data of GSE1297 series is downloaded from Gene Expression Omnibus (GEO). Significance analysis of microarray is performed usingsoftware R, and differentially expressed genes (DEGs) are harvested. The functions and pathways of DEGs are mapped in Gene Otology and KEGG pathway database respectively. A total of 2273 genes are filtered as DEGs between normal and Alzheimer’s disease cells. This research work is to depict the molecular level changes of Alzheimer disease through microarray analysis of differentially expressed genes (DEGs), and the function and pathway enrichment of differentially expressed genes (DEGs).
  • 关键词:Gene Enrichment Analysis;Pathway Analysis;Differentially Expressed Genes
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