title: Pattern classification of phylogeny signals.
abstract: In this paper we propose the minimum entropy clustering (MEC) method for clustering genes based on their phylogenetic signals. This entropy based method will cluster two genes together when their concatenation can decrease the entropy. An integral feature of MEC is that it chooses the number of clusters automatically, which is a major advantage over the other methods. Our simulation results show that this method is quite successful in clustering genes with a common phylogeny.
authors.affiliation: Dalhousie University. shi@mathstat.dal.ca
authors.forename: Xiaofei
authors.initials: X
authors.lastname: Shi
authors.forename: Hong
authors.initials: H
authors.lastname: Gu
authors.forename: Chris
authors.initials: C
authors.lastname: Field
mesh_terms: D000465:Algorithms; D000818:Animals; D016000:Cluster Analysis; D003198:Computer Simulation; D019277:Entropy; D004926:Escherichia coli / Q000235:genetics; D019143:Evolution, Molecular; D005798:Genes, Bacterial; D017344:Genes, Insect; D006193:Haemophilus influenzae / Q000235:genetics; D007257:Information Theory; D016013:Likelihood Functions; D005810:Multigene Family; D016979:Pasteurella multocida / Q000235:genetics; D010363:Pattern Recognition, Automated / Q000379:methods*; D010802:Phylogeny; D012486:Salmonella typhimurium / Q000235:genetics; D016415:Sequence Alignment; D013559:Symbiosis / Q000235:genetics; D014734:Vibrio cholerae / Q000235:genetics; D015007:Yersinia / Q000235:genetics