• Dec 20, 2017 News!ACMLC 2017 has been successfully held in NEC, Singapore during December 8-10.   [Click]
  • Dec 12, 2017 News!Good News! All papers from Volume 7, Number 1 to Volume 7, Number 5 have been indexed by Scopus!   [Click]
  • Mar 05, 2018 News!Welcome Assoc. Prof. Xianghua Xie, University of Swansea, UK joins our editorial board.
General Information
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2014 Vol. 4(6): 538-542 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2014.V6.469

Similarity/Dissimilarity of DNA Sequences Based on a New Condensed Curve Representation

Qianjun Xiao
Abstract—Based on a 3-D graphical representation, Bo Liao et al. [B. Liao et al., J. Molec. Struct. (THEOCHEM) 717 (2005) 199] made a comparison for the coding sequences of the first exon of β-globin gene of 11 different species. However, some results in the Tables IV of Liao's were somewhat rational because the main information focus on the cumulative occurrence numbers Si of base A, G, C, T. In this paper, we propose another 3D graphical representation by converting the Si into 1-1/Si. Based on the mathematic invariants S2, the results of comparison for the coding sequences used in Liao's are improved greatly and the examination of similarities among the full coding sequences shows our graphical representation method is more effective to the comparative study of DNA sequences. Furthermore, our graphical curves are compact and the complexities of computation are very small especially for long sequences.

Index Terms—DNA Sequences, graphical representation, numerical characterization, S2, similarity.

Qianjun Xiao is now with Hunan Vocational Institute of Technology, Xiangtan 411104, China (tel.: +86-731-52720616; e-mail: xqjxt@126.com, qjxiao1978@126.com).


Cite: Qianjun Xiao, "Similarity/Dissimilarity of DNA Sequences Based on a New Condensed Curve Representation," International Journal of Machine Learning and Computing vol. 4, no. 6, pp. 538-542, 2014.

Copyright © 2008-2018. International Journal of Machine Learning and Computing. All rights reserved.
E-mail: ijmlc@ejournal.net