Chao J, Tang F, Xu L. Developments in Algorithms for Sequence Alignment: A Review.
Biomolecules 2022;
12:biom12040546. [PMID:
35454135 PMCID:
PMC9024764 DOI:
10.3390/biom12040546]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 03/29/2022] [Accepted: 03/31/2022] [Indexed: 01/27/2023] Open
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.
Collapse