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Genetic algorithm based two-mode clustering of metabolomics data
2008
Metabolomics
Metabolomics and other omics tools are generally characterized by large data sets with many variables obtained under different environmental conditions. Clustering methods and more specifically two-mode clustering methods are excellent tools for analyzing this type of data. Two-mode clustering methods allow for analysis of the behavior of subsets of metabolites under different experimental conditions. In addition, the results are easily visualized. In this paper we introduce a two-mode
doi:10.1007/s11306-008-0105-7
fatcat:i6oadxgaffccfjygnttlgcm47u