Interpolated variable order motifs for identification of horizontally acquired DNA: revisiting the Salmonella pathogenicity islands
Author(s) -
Georgios S Vernikos,
Julian Parkhill
Publication year - 2006
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btl369
Subject(s) - computational biology , genome , horizontal gene transfer , pathogenicity island , biology , hidden markov model , salmonella enterica , genetics , comparative genomics , computer science , genomics , data mining , salmonella , gene , artificial intelligence , bacteria
There is a growing literature on the detection of Horizontal Gene Transfer (HGT) events by means of parametric, non-comparative methods. Such approaches rely only on sequence information and utilize different low and high order indices to capture compositional deviation from the genome backbone; the superiority of the latter over the former has been shown elsewhere. However even high order k-mers may be poor estimators of HGT, when insufficient information is available, e.g. in short sliding windows. Most of the current HGT prediction methods require pre-existing annotation, which may restrict their application on newly sequenced genomes.
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