Applying Clustering and Phylogeny Analysis to Study Dinoflagellates Based on Sterol Composition

• Published in: 2008 IEEE International Conference on Bioinformatics and Biomedicine pp. 90 - 97
• Main Authors: Leblond, J.D., Lasiter, A.D., Cen Li, Logares, R., Rengefors, K., Evens, T.J.
• Format: Conference Proceeding Journal Article
• Language: English
• Published: IEEE 01-01-2008
• Subjects: Bayesian methods; Biomarkers; cluster validation; clustering; Clustering algorithms; Data analysis; dinoflagellate; Euclidean distance; History; Organisms; Partitioning algorithms; Phylogeny; sterol; USA Councils
• ISBN: 076953452X; 9780769534527
• DOI: 10.1109/BIBM.2008.16

This study examined the sterol compositions of 102 dinoflagellates (including several previously unexamined species) using clustering techniques as a means of determining the relatedness of the organisms. In addition, dinoflagellate sterol-based relationships were compared statistically to dinoflagellate 18S rDNA-based phylogeny relationships using the Mantel test. Our results indicated that the examined dinoflagellates form six clusters based on sterol composition and that several, but not all, dinoflagellate genera that form discrete clusters in the 18S rDNA-based phylogeny share 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.