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Developments in Algorithms for Sequence Alignment: A Review.
Chao, Jiannan; Tang, Furong; Xu, Lei.
  • Chao J; Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China.
  • Tang F; Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou 324003, China.
  • Xu L; School of Electronic and Communication Engineering, Shenzhen Polytechnic, Shenzhen 518055, China.
Biomolecules ; 12(4)2022 04 06.
Article in English | MEDLINE | ID: covidwho-1809687
ABSTRACT
The continuous development of sequencing technologies has enabled researchers to obtain large amounts of biological sequence data, and this has resulted in increasing demands for software that can perform sequence alignment fast and accurately. A number of algorithms and tools for sequence alignment have been designed to meet the various needs of biologists. Here, the ideas that prevail in the research of sequence alignment and some quality estimation methods for multiple sequence alignment tools are summarized.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Algorithms / Software Language: English Year: 2022 Document Type: Article Affiliation country: Biom12040546

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Algorithms / Software Language: English Year: 2022 Document Type: Article Affiliation country: Biom12040546