Sequence similarity alignment algorithm in bioinformatics: techniques and challenges

Yuren Liu, Yijun Yan, Jinchang Ren

Research output: Chapter in Book/Report/Conference proceedingConference contribution book


Sequence similarity alignment is a basic information processing method in bioinformatics. It is very important for discovering the information of function, structure and evolution in biological sequences. The main idea is to use a specific mathematical model or algorithm to find the maximum matching base or residual number between two or more sequences. The results of alignment reflect to what extent the algorithm reflects the similarity relationship between sequences and their biological characteristics. Therefore, the simple and effective algorithm of sequence similarity alignment in bioinformatics has always been a concern of biologists. This paper reviews some widely used sequence alignment algorithms including double-sequence alignment and multi-sequence alignment, simultaneously, introduces a method to call genetic variants from next-generation gene sequence data.
Original languageEnglish
Title of host publicationAdvances in Brain Inspired Cognitive Systems
Subtitle of host publication10th International Conference, BICS 2019, Guangzhou, China, July 13–14, 2019, Proceedings
EditorsJinchang Ren, Amir Hussain, Huimin Zhao, Kaizhu Huang, Jiangbin Zheng, Jun Cai, Rongjun Chen, Yinyin Xiao
Place of PublicationCham, Switzerland
Number of pages11
ISBN (Electronic)9783030394318
ISBN (Print)9783030394301
Publication statusPublished - 1 Feb 2020
Event10th International Conference on Brain Inspired Cognitive Systems, BICS 2019 - Guangzhou, China
Duration: 13 Jul 201914 Jul 2019


Conference10th International Conference on Brain Inspired Cognitive Systems, BICS 2019


  • bioinformatics
  • longest common subsequence (LCS)
  • deoxyribonucleic acid (DNA)
  • sequence alignment

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