Analyzing Microarray Data of Alzheimer's Using Cluster Analysis to Identify the Biomarker Genes | Zendy

Satya vani Guttula | Zendy; A. Apparao | Zendy; Ramachandra Sridhar Gumpeny | Zendy

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Analyzing Microarray Data of Alzheimer's Using Cluster Analysis to Identify the Biomarker Genes

Author(s) -

Satya vani Guttula,

A. Apparao,

Ramachandra Sridhar Gumpeny

Publication year - 2012

Publication title -

international journal of alzheimer s disease

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.657

H-Index - 49

eISSN - 2090-8024

pISSN - 2090-0252

DOI - 10.1155/2012/649456

Subject(s) - senile plaques , gene , biomarker , microarray analysis techniques , microarray , computational biology , apolipoprotein e , gene expression , biology , alzheimer's disease , pathology , medicine , genetics , disease

Alzheimer is characterized by the presence of senile plaques and neurofibrillary tangles in cortical regions of the brain. The experimental data is taken from Gene Expression Omnibus. A hierarchical Cluster analysis and TreeView were performed to group genes on the basis of the expression pattern. The dynamic change of expression over time and diverse patterns of expression support the concept of a complex local milieu. TreeView allows the organized data to be visualized. List of 24 genes were obtained which showed high expression levels. Three genes, SORL1, APP, and APOE, are suspected to cause Alzheimer's whereas the other 21 genes are related to other diseases but may also be found to be associated with Alzheimer's, and these are TMEM59, CCT4, IGF2R, SFPQ, PRDX3, RNF14, IDS, SSBP1, SYNE2, TXNL4A, STXBP3, SMARCB1, ULK2, AGTPBP1, FABP7, CALB1, H2AFY, COPA, SAP18, ATIC and SYNCRIP.

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