Paper: Genetic algorithm based two-mode clustering of metabolomics data

Jos Hageman (UvA, now Biometris in Wageningen) published the paper Genetic algorithm based two-mode clustering of metabolomics data (DOI:10.1007/s11306-008-0105-7):

In this paper we introduce a two-mode clustering method based on a genetic algorithm that uses a criterion that searches for homogeneous clusters. Furthermore we introduce a cluster stability criterion to validate the clusters and we provide an extended knee plot to select the optimal number of clusters in both experimental and metabolite modes. The genetic algorithm-based two-mode clustering gave biological relevant results when it was applied to two real life metabolomics data sets.

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