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A data mining approach to dinoflagellate clustering according to sterol composition: correlations with evolutionary history

Leblond, Jeffrey D; Lasiter, Andew D; Li, Cen; Logares, Ramiro; Rengefors, Karin LU and Evens, Terence J. (2010) In International Journal of Data Mining and Bioinformatics 4(4). p.431-451
Abstract (Swedish)
Abstract in Undetermined

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... (More)
Abstract in Undetermined

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. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
bioinformatics, clustering, cluster validation, data mining, dinoflagellate, knowledge discovery, phylogeny analysis, sterol
in
International Journal of Data Mining and Bioinformatics
volume
4
issue
4
pages
431 - 451
publisher
Inderscience
external identifiers
  • wos:000280011800005
  • scopus:77954752951
ISSN
1748-5673
DOI
10.1504/IJDMB.2010.034198
language
English
LU publication?
yes
id
01868a90-b5c4-4404-9413-de67c4669c81 (old id 1445406)
date added to LUP
2009-08-10 13:59:26
date last changed
2018-05-29 10:22:31
@article{01868a90-b5c4-4404-9413-de67c4669c81,
  abstract     = {<b>Abstract in Undetermined</b><br/><br>
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.},
  author       = {Leblond, Jeffrey D and Lasiter, Andew D and Li, Cen and Logares, Ramiro and Rengefors, Karin and Evens, Terence J.},
  issn         = {1748-5673},
  keyword      = {bioinformatics,clustering,cluster validation,data mining,dinoflagellate,knowledge discovery,phylogeny analysis,sterol},
  language     = {eng},
  number       = {4},
  pages        = {431--451},
  publisher    = {Inderscience},
  series       = {International Journal of Data Mining and Bioinformatics},
  title        = {A data mining approach to dinoflagellate clustering according to sterol composition: correlations with evolutionary history},
  url          = {http://dx.doi.org/10.1504/IJDMB.2010.034198},
  volume       = {4},
  year         = {2010},
}