By Topic

Nearest hyperplane distance neighbor clustering algorithm applied to gene co-expression analysis in Alzheimer's disease

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Pasluosta, C.F. ; Dept. of Health Inf. & Inf. Manage., Louisiana Tech Univ., Ruston, LA, USA ; Dua, P. ; Lukiw, W.J.

Microarray analysis can contribute considerably to the understanding of biologically significant cellular mechanisms that yield novel information regarding co-regulated sets of gene patterns. Clustering is one of the most popular tools for analyzing DNA microarray data. In this paper, we present an unsupervised clustering algorithm based on the K-local hyperplane distance nearest-neighbor classifier (HKNN). We adapted the well-known nearest neighbor clustering algorithm for use with hyperplane distance. The result is a simple and computationally inexpensive unsupervised clustering algorithm that can be applied to high-dimensional data. It has been reported that the NFkB1 gene is progressively over-expressed in moderate-to-severe Alzheimer's disease (AD) cases, and that the NF-kB complex plays a key role in neuroinflammatory responses in AD pathogenesis. In this study, we apply the proposed clustering algorithm to identify co-expression patterns with the NFkB1 in gene expression data from hippocampal tissue samples. Finally, we validate our experiments with biomedical literature search.

Published in:

Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE

Date of Conference:

Aug. 30 2011-Sept. 3 2011