Literature DB >> 23147229

A novel statistical measure for sequence comparison on the basis of k-word counts.

Xiwu Yang1, Tianming Wang.   

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.
Copyright © 2012 Elsevier Ltd. All rights reserved.

Mesh:

Substances:

Year:  2012        PMID: 23147229     DOI: 10.1016/j.jtbi.2012.10.035

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  3 in total

1.  K-mer natural vector and its application to the phylogenetic analysis of genetic sequences.

Authors:  Jia Wen; Raymond H F Chan; Shek-Chung Yau; Rong L He; Stephen S T Yau
Journal:  Gene       Date:  2014-05-22       Impact factor: 3.688

2.  Phylogenetic Analysis of HIV-1 Genomes Based on the Position-Weighted K-mers Method.

Authors:  Yuanlin Ma; Zuguo Yu; Runbin Tang; Xianhua Xie; Guosheng Han; Vo V Anh
Journal:  Entropy (Basel)       Date:  2020-02-23       Impact factor: 2.524

3.  A new graph-theoretic approach to determine the similarity of genome sequences based on nucleotide triplets.

Authors:  Subhram Das; Arijit Das; D K Bhattacharya; D N Tibarewala
Journal:  Genomics       Date:  2020-08-19       Impact factor: 5.736

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.