title: CAGE: Combinatorial Analysis of Gene-cluster Evolution.
abstract: Much important evolutionary activity occurs in gene clusters, where a copy of a gene may be free to acquire new functions. Current computational methods to extract evolutionary information from sequence data for such clusters are suboptimal, in part because accurate sequence data are often lacking in these genomic regions, making existing methods difficult to apply. We describe a new method for reconstructing the recent evolutionary history of gene clusters, and evaluate its performance on both simulated data and actual human gene clusters.
authors.affiliation: Center for Comparative Genomics and Bioinformatics, Penn State University, University Park, PA 16802, USA. gsong@bx.psu.edu
authors.forename: Giltae
authors.initials: G
authors.lastname: Song
authors.forename: Louxin
authors.initials: L
authors.lastname: Zhang
authors.forename: Tomas
authors.initials: T
authors.lastname: Vinar
authors.forename: Webb
authors.initials: W
authors.lastname: Miller
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D016000:Cluster Analysis; D023082:Defensins / Q000235:genetics; D019143:Evolution, Molecular; D020440:Gene Duplication; D006801:Humans; D008957:Models, Genetic; D008969:Molecular Sequence Data; D005810:Multigene Family; D010802:Phylogeny
chemical_list: D023082:Defensins