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Yin, Z., Zhou, X.B., Bakal, C., Li1, F.H., Sun, Y.X., Perrimon, N. and Wong, S.T.C. (2008) Using iterative cluster merging with improved gap statistics to perform online phenotype discovery in the context of high-throughput RNAi screensBMC. Bioinformatics, 9, 264.

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• TITLE: Estimating the number of data clusters via the contrast statistic

  AUTHORS: Yuriy Lyakh, Vitaliy Gurianov, Oleg Gorshkov, Yuriy Vihovanets

  KEYWORDS: SOM Neural Network; Clustering; Gap Statistic; Silhouette Statistic

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.5 No.2, February 28, 2012

  ABSTRACT: A new method (the Contrast statistic) for estimating the number of clusters in a set of data is proposed. The technique uses the output of self-organising map clustering algorithm, comparing the change in dependency of “Contrast” value upon clusters number to that expected under a uniform distribution. A simulation study shows that the Contrast statistic can be used successfully either, when variables describing the object in a multi-dimensional space are independent (ideal objects) or dependent (real biological objects).