title: A novel statistical measure for sequence comparison on the basis of k-word counts.
abstract: Numerous efficient methods based on word counts for sequence analysis have been proposed to characterize DNA sequences to help in comparison, retrieval from the databases and reconstructing evolutionary relations. However, most of them seem unrelated to any intrinsic characteristics of DNA. In this paper, we proposed a novel statistical measure for sequence comparison on the basis of k-word counts. This new measure removed the influence of sequences' lengths and uncovered bulk property of DNA sequences. The proposed measure was tested by similarity search and phylogenetic analysis. The experimental assessment demonstrated that our similarity measure was efficient.
authors.affiliation: School of Mathematical Sciences, Dalian University of Technology, Dalian, Liaoning 116024, PR China. cinema@lnnu.edu.cn
authors.forename: Xiwu
authors.initials: X
authors.lastname: Yang
authors.forename: Tianming
authors.initials: T
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000379:methods; D004272:DNA, Mitochondrial / Q000235:genetics; D004279:DNA, Viral / Q000235:genetics; D003627:Data Interpretation, Statistical; D016752:Hepatitis E virus / Q000235:genetics; D006801:Humans; D010802:Phylogeny; D012372:ROC Curve; D016415:Sequence Alignment / Q000379:methods; D017422:Sequence Analysis, DNA / Q000379:methods*
chemical_list: D004272:DNA, Mitochondrial; D004279:DNA, Viral