title: KODAMA: an R package for knowledge discovery and data mining.
abstract: 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.
  
  
  
  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).
  
  
  
  s.cacciatore@imperial.ac.uk.
  
  
  
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Institute of Reproductive and Developmental Biology, Imperial College London, London, UK.
authors.forename: Stefano
authors.initials: S
authors.lastname: Cacciatore
authors.affiliation: Department of Clinical and Experimental Medicine.
authors.forename: Leonardo
authors.initials: L
authors.lastname: Tenori
authors.affiliation: Centro Risonanze Magnetiche, University of Florence, Florence, Italy.
authors.forename: Claudio
authors.initials: C
authors.lastname: Luchinat
authors.affiliation: Institute of Reproductive and Developmental Biology, Imperial College London, London, UK.
authors.forename: Phillip R
authors.initials: PR
authors.lastname: Bennett
authors.affiliation: Institute of Reproductive and Developmental Biology, Imperial College London, London, UK.
authors.forename: David A
authors.initials: DA
authors.lastname: MacIntyre
mesh_terms: D000465:Algorithms; D057225:Data Mining / Q000379:methods*; D005260:Female; D006801:Humans; D009682:Magnetic Resonance Spectroscopy / Q000379:methods; D008297:Male; D012984:Software; D000069558:Unsupervised Machine Learning; D016482:Urinalysis / Q000379:methods