KODAMA: an R package for knowledge discovery and data mining

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 packag...

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Autores principales: Cacciatore, Stefano, Tenori, Leonardo, Luchinat, Claudio, Bennett, Phillip R, MacIntyre, David A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Applications Notes
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408808/
https://www.ncbi.nlm.nih.gov/pubmed/27993774
http://dx.doi.org/10.1093/bioinformatics/btw705
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author Cacciatore, Stefano
Tenori, Leonardo
Luchinat, Claudio
Bennett, Phillip R
MacIntyre, David A
author_facet Cacciatore, Stefano
Tenori, Leonardo
Luchinat, Claudio
Bennett, Phillip R
MacIntyre, David A
author_sort Cacciatore, Stefano
collection PubMed
description 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.
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spelling pubmed-54088082017-05-03 KODAMA: an R package for knowledge discovery and data mining Cacciatore, Stefano Tenori, Leonardo Luchinat, Claudio Bennett, Phillip R MacIntyre, David A Bioinformatics Applications Notes 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. Oxford University Press 2017-02-15 2016-11-30 /pmc/articles/PMC5408808/ /pubmed/27993774 http://dx.doi.org/10.1093/bioinformatics/btw705 Text en © The Author 2016. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Cacciatore, Stefano
Tenori, Leonardo
Luchinat, Claudio
Bennett, Phillip R
MacIntyre, David A
KODAMA: an R package for knowledge discovery and data mining
title KODAMA: an R package for knowledge discovery and data mining
title_full KODAMA: an R package for knowledge discovery and data mining
title_fullStr KODAMA: an R package for knowledge discovery and data mining
title_full_unstemmed KODAMA: an R package for knowledge discovery and data mining
title_short KODAMA: an R package for knowledge discovery and data mining
title_sort kodama: an r package for knowledge discovery and data mining
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408808/
https://www.ncbi.nlm.nih.gov/pubmed/27993774
http://dx.doi.org/10.1093/bioinformatics/btw705
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