Fuzzy Clustering improves Phylogenetic Relationships Reconstruction from Metabolic Pathways
نویسندگان
چکیده
The interest in reconstructing phylogenetic relationships from data on structural similarity of metabolic pathways is growing. The similarity notions and the techniques involved in this reconstruction are assessed by building phylogenetic relationships for model sets of organisms from the similarity measures of the same metabolic pathway for all of them, and then the phylogenetic trees obtained are compared to the NCBI taxonomy. The best technique proposed so far is due to some of the authors of this paper [2], using a new similarity relation for metabolic pathways and average-link hierarchical clustering to compute the phylogenetic tree. In this paper we prove that using a fuzzy clustering method to compute the phylogenetic relationships from this similarity relation the resulting trees are usually closer to the NCBI taxonomy.
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