| Literature DB >> 28763687 |
Xin Jin1, Qian Jiang1, Yanyan Chen2, Shin-Jye Lee3, Rencan Nie1, Shaowen Yao4, Dongming Zhou5, Kangjian He1.
Abstract
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.Keywords: DNA sequence analysis; Evolutionary relationship; Feature extraction; Graphical representation; Similarity analysis
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Year: 2017 PMID: 28763687 DOI: 10.1016/j.jmgm.2017.07.019
Source DB: PubMed Journal: J Mol Graph Model ISSN: 1093-3263 Impact factor: 2.518