4.5 Article

Similarity/dissimilarity calculation methods of DNA sequences: A survey

Journal

JOURNAL OF MOLECULAR GRAPHICS & MODELLING
Volume 76, Issue -, Pages 342-355

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.jmgm.2017.07.019

Keywords

DNA sequence analysis; Similarity analysis; Graphical representation; Evolutionary relationship; Feature extraction

Funding

  1. National Natural Science Foundation of China [61640306]
  2. Key Laboratory of Software Engineering of Yunnan Province in China [2017SE202]
  3. Scientific Research Fund of Education Department of Yunnan Province in China [2017YJS108]
  4. Doctoral Candidate Academic Award of Yunnan Province in China

Ask authors/readers for more resources

DNA sequence similarity/dissimilarity analysis is a fundamental task in computational biology, which is used to analyze the similarity of different DNA sequences for learning their evolutionary relationships. In past decades, a large number of similarity analysis methods for DNA sequence have been proposed due to the ever-growing demands. In order to learn the advances of DNA sequence similarity analysis, we make a survey and try to promote the development of this field. In this paper, we first introduce the related knowledge of DNA similarities analysis, including the data sets, similarities distance and output data. Then, we review recent algorithmic developments for DNA similarity analysis to represent a survey of the art in this field. At last, we summarize the corresponding tendencies and challenges in this research field. This survey concludes that although various DNA similarity analysis methods have been proposed, there still exist several further improvements or potential research directions in this field. (C) 2017 Elsevier Inc. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available