Journal of Computational Biology and Bioinformatics Research
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Article Number - C3BA24A8509


Vol.2(1), pp. 001-004 , March 2010

ISSN: 2141-2227



Full Length Research Paper

ClustPK: A windows-based cluster analysis tool


Masood ur Rehman Kayani, Umair Shahzad Alam, Farida Anjum and Asif Mir*




Department of Biosciences,COMSATS Institute of Information Technology, Bio-Physics Block, Chak Shahzad Campus, Islamabad-44000, Pakistan.


Email: asif_mir@comsats.edu.pk






 Accepted: 22 October 2009  Published: 31 March 2010

Copyright © 2010 Author(s) retain the copyright of this article.
This article is published under the terms of the Creative Commons Attribution License 4.0


There is a great need to develop analytical methodologies to analyze and exploit the information contained in gene expression data obtained from microarray-based experiments. Because of large number of genes and complexity of biological networks, clustering is a useful exploratory technique for analysis of such data. Different data analysis techniques and algorithms have been developed which are used to cluster the gene expression data. Various tools have been developed that implement these algorithms. Clusters of co-expressed genes provide useful basis for further investigation of gene function, regulation and their possible involvement in causing different diseases. ClustPK has been developed using C# .NET and implementing k-means and PCA algorithms. Analysis of microarray data using the already existing tools is difficult and the results are also hard to be analyzed. While, ClustPK is an easy-to-use and user friendly tool that provides the easy visualization and analysis of the results obtained from eitherk-means or PCA.

 

Key words: Microarray, gene expression, data sets, cluster analysis, k-means, principle component analysis.

Abbreviation:
C#; C Sharp, PC; Principle Component, PCA; Principle Component Analysis


APA (2010). ClustPK: A windows-based cluster analysis tool. Journal of Computational Biology and Bioinformatics Research, 2(1), 001-004.
Chicago Masood ur Rehman Kayani, Umair Shahzad Alam, Farida Anjum and Asif Mir. "ClustPK: A windows-based cluster analysis tool." Journal of Computational Biology and Bioinformatics Research 2, no. 1 (2010): 001-004.
MLA Masood ur Rehman Kayani, et al. "ClustPK: A windows-based cluster analysis tool." Journal of Computational Biology and Bioinformatics Research 2.1 (2010): 001-004.
   
DOI
URL http://academicjournals.org/journal/JCBBR/article-abstract/C3BA24A8509

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