Title :
The strong correlation of gene expression data on Alzheimer´s disease and co-regulation of gene
Author :
Pang, Chao-Yang ; Yang, Long ; Zhang, Dan-Xia ; Xia, Xiao-Pei ; Hu, Ben-Qiong
Author_Institution :
Group of Gene Comput., Key Lab. of Visual Comput. & Virtual Reality of Sichuan Province, Chengdu, China
Abstract :
Alzheimer´s disease (AD) is the most common form of dementia, little is known about its complicated mechanisms. To deeply understand its mechanisms, DNA microarray expression profiling and its analysis appears particularly promising. In this paper, the correlation of the DNA microarray expression data which is downloaded from GEO Datasets, NCBI [1], is analyzed via Principal Component Analysis (PCA), the character of strong linear correlation is observed. And this character implies that the information of gene co-regulation is mapped into the compactness of clustering of expression data possibly (i.e., all data clustering tightly in different classes). Thus, through the computerized compactness, the potential co-regulated genes can be identified.
Keywords :
diseases; genetics; lab-on-a-chip; medical disorders; particle swarm optimisation; Alzheimer disease; DNA microarray expression data correlation; GEO datasets; computerized compactness; dementia; expression data clustering; gene co-regulation; gene expression data; linear correlation; principal component analysis; Alzheimer´s disease; Correlation; Educational institutions; Gene expression; Principal component analysis; Vectors; Alzheimer´s disease; DNA Microarray Data; Gene; Principal Component Analysis;
Conference_Titel :
Granular Computing (GrC), 2011 IEEE International Conference on
Conference_Location :
Kaohsiung
Print_ISBN :
978-1-4577-0372-0
DOI :
10.1109/GRC.2011.6122713