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Oxford University Press, Bioinformatics, 4(33), p. 621-623, 2016

DOI: 10.1093/bioinformatics/btw705

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KODAMA: an R package for knowledge discovery and data mining

Journal article published in 2016 by Stefano Cacciatore, Leonardo Tenori, Claudio Luchinat, Pr Bennett, Da MacIntyre ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Abstract Summary KODAMA, a novel learning algorithm for unsupervised feature extraction, is specifically designed for analysing noisy and high-dimensional datasets. Here we present an R package of the algorithm with additional functions that allow improved interpretation of high-dimensional data. The package requires no additional software and runs on all major platforms. Availability and Implementation KODAMA is freely available from the R archive CRAN (http://cran.r-project.org). The software is distributed under the GNU General Public License (version 3 or later). Supplementary information Supplementary data are available at Bioinformatics online.