A data mining approach to dinoflagellate clustering according to sterol composition: correlations with evolutionary history. (19th July 2010)

• Record Type: Journal Article
• Authors: Leblond, Jeffrey D.; Lasiter, Andrew D.; Li, Cen; Logares, Ramiro; Rengefors, Karin; Evens, Terence
• Is Part Of: International journal of data mining and bioinformatics. Volume 4:Number 4(2010)
• Page Start: 431
• Page End: 451
• Publication Date: 2010-07-19
• Subjects: bioinformatics -- dinoflagellate clustering -- cluster validation -- data mining -- knowledge discovery -- phylogeny analysis -- sterol composition -- dinoflagellates -- evolutionary history; Data mining -- Periodicals; Bioinformatics -- Periodicals; 006.312
• Languages: English
• ISSNs: 1748-5673

Abstract

This study examined the sterol compositions of 102 dinoflagellates using clustering and cluster validation techniques, as a means of determining the relatedness of the organisms. In addition, dinoflagellate sterol-based relationships were compared statistically to 18S rDNA-based phylogenetic relationships using the Mantel test. Our results indicated that the examined dinoflagellates formed six clusters based on sterol composition and that several, but not all, dinoflagellate genera, which formed discrete clusters in the 18S rDNA-based phylogeny, shared similar sterol compositions. This and other correspondences suggest that the sterol compositions of dinoflagellates are explained, to a certain extent, by the evolutionary history of this lineage.