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2011 IEEE 11th International Conference on Bioinformatics and Bioengineering (2011)
Taichung, Taiwan
Oct. 24, 2011 to Oct. 26, 2011
ISBN: 978-0-7695-4391-8
pp: 299-302
ABSTRACT
Measurement of gene expression using DNA micro arrays have revolutionized biological and medical research. This paper presents a divisive clustering algorithm that produces a tree of genes called GERC tree along with the generated clusters. Unlike a dendrogram, a GERC tree is a general tree and it is an ample resource for biological information about the genes in a data set. The leaves of the tree represent the desired clusters. The clustering method was tested with several real-life data sets and the proposed method has been found satisfactory.
INDEX TERMS
Hierarchical Clustering, Recursive Clustering, Gene Expression Data, Mean Squared Residue
CITATION

P. Mahanta, J. K. Kalita, D. Bhattacharyya and H. Ahmed, "GERC: Tree Based Clustering for Gene Expression Data," 2011 IEEE 11th International Conference on Bioinformatics and Bioengineering(BIBE), Taichung, Taiwan, 2011, pp. 299-302.
doi:10.1109/BIBE.2011.54
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