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A Simpler and More Accurate AUTO-HDS Framework for Clustering and Visualization of Biological Data
Nov.-Dec. 2012 (vol. 9 no. 6)
pp. 1850-1852
R. J. G. B. Campello, Dept. of Comput. Sci., Univ. of Alberta, Edmonton, AB, Canada
D. Moulavi, Dept. of Comput. Sci., Univ. of Alberta, Edmonton, AB, Canada
J. Sander, Dept. of Comput. Sci., Univ. of Alberta, Edmonton, AB, Canada
In [1], the authors proposed a framework for automated clustering and visualization of biological data sets named AUTO-HDS. This letter is intended to complement that framework by showing that it is possible to get rid of a userdefined parameter in a way that the clustering stage can be implemented more accurately while having reduced computational complexity.
Index Terms:
pattern clustering,bioinformatics,computational complexity,data mining,data visualisation,computational complexity,AUTO-HDS framework,biological data clustering,biological data visualization,Clustering algorithms,Complexity theory,Data mining,Data visualization,Bioinformatics,AUTO-HDS,Data mining,clustering,bioinformatics databases
Citation:
R. J. G. B. Campello, D. Moulavi, J. Sander, "A Simpler and More Accurate AUTO-HDS Framework for Clustering and Visualization of Biological Data," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 9, no. 6, pp. 1850-1852, Nov.-Dec. 2012, doi:10.1109/TCBB.2012.115
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