jClust: A clustering and visualization toolbox

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Abstract

jClust is a user-friendly application which provides access to a set of widely used clustering and clique finding algorithms. The toolbox allows a range of filtering procedures to be applied and is combined with an advanced implementation of the Medusa interactive visualization module. These implemented algorithms are κ-Means, Affinity propagation, Bron-Kerbosch, MULIC, Restricted neighborhood search cluster algorithm, Markov clustering and Spectral clustering, while the supported filtering procedures are haircut, outside-inside, best neighbors and density control operations. The combination of a simple input file format, a set of clustering and filtering algorithms linked together with the visualization tool provides a powerful tool for data analysis and information extraction. © 2009 The Author(s).

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Pavlopoulos, G. A., Moschopoulos, C. N., Hooper, S. D., Schneider, R., & Kossida, S. (2009). jClust: A clustering and visualization toolbox. Bioinformatics, 25(15), 1994–1996. https://doi.org/10.1093/bioinformatics/btp330

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