Quad-Tree Based Multiple Kernel Fuzzy C-Means Clustering for Gene Expression Data
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International Journal of Computer Trends and Technology (IJCTT) | 
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| © 2015 by IJCTT Journal | ||
| Volume-27 Number-3 |
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| Year of Publication : 2015 | ||
| Authors : E. Monica Sushil Cynthia, S. Kannan | ||
| DOI : 10.14445/22312803/IJCTT-V27P121 |
E. Monica Sushil Cynthia, S. Kannan "Quad-Tree Based Multiple Kernel Fuzzy C-Means Clustering for Gene Expression Data". International Journal of Computer Trends and Technology (IJCTT) V27(3):121-125, September 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
Minute variations in genes can have a
major impact on how humans respond to disease,
environmental factors such as bacteria, viruses,
toxins, chemicals and drugs and other therapies..
Cluster analysis seeks to partition a given data set
into groups based on specified features so that the
data points within a group are more similar to each
other than the points in different groups. The
clustering algorithms have been proven useful for
identifying biologically relevant groups of genes and
samples. Hence in this paper we propose a new
clustering algorithm for gene expression data
associated to three different types of cancer and also
compare with the existing approaches to prove the
novel approach proposed here, has a better
performance, reliability and provide more
meaningful biological significance.
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Keywords
Clustering, Clustering Algorithms, Gene
Expression analysis, Fuzzy C-Means, Hierarchical
Clustering, Gene Clustering, Gene Expression data,
Quad Tree, Kernel fuzzy C-means.