Sequence similarity alignment algorithm in bioinformatics: Techniques and challenges

Yuren Liu; Yijun Yan; Jinchang Ren; Stephen Marshall

doi:10.1007/978-3-030-39431-8_53

Sequence similarity alignment algorithm in bioinformatics: Techniques and challenges

Yuren Liu, Yijun Yan, Jinchang Ren (Lead / Corresponding author), Stephen Marshall

Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

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 language	English
Title of host publication	Advances in Brain Inspired Cognitive Systems
Subtitle of host publication	10th International Conference, BICS 2019, Guangzhou, China, July 13–14, 2019, Proceedings
Editors	Jinchang Ren, Amir Hussain, Huimin Zhao, Jun Cai, Rongjun Chen, Yinyin Xiao, Kaizhu Huang, Jiangbin Zheng
Place of Publication	Switzerland
Publisher	Springer
Pages	550-560
Number of pages	11
Edition	1
ISBN (Electronic)	9783030394318
ISBN (Print)	9783030394301
DOIs	https://doi.org/10.1007/978-3-030-39431-8_53
Publication status	Published - 1 Feb 2020
Event	10th International Conference on Brain Inspired Cognitive Systems, BICS 2019 - Guangzhou, China Duration: 13 Jul 2019 → 14 Jul 2019

Publication series

Name	Lecture Notes in Computer Science
Volume	11691
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th International Conference on Brain Inspired Cognitive Systems, BICS 2019
Country/Territory	China
City	Guangzhou
Period	13/07/19 → 14/07/19

Keywords

Bioinformatics
Deoxyribonucleic acid (DNA)
Longest common subsequence (LCS)
Sequence alignment

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-39431-8_53

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Liu, Y., Yan, Y., Ren, J., & Marshall, S. (2020). Sequence similarity alignment algorithm in bioinformatics: Techniques and challenges. In J. Ren, A. Hussain, H. Zhao, J. Cai, R. Chen, Y. Xiao, K. Huang, & J. Zheng (Eds.), Advances in Brain Inspired Cognitive Systems: 10th International Conference, BICS 2019, Guangzhou, China, July 13–14, 2019, Proceedings (1 ed., pp. 550-560). (Lecture Notes in Computer Science; Vol. 11691). Springer . https://doi.org/10.1007/978-3-030-39431-8_53

Liu, Yuren ; Yan, Yijun ; Ren, Jinchang et al. / Sequence similarity alignment algorithm in bioinformatics : Techniques and challenges. Advances in Brain Inspired Cognitive Systems: 10th International Conference, BICS 2019, Guangzhou, China, July 13–14, 2019, Proceedings. editor / Jinchang Ren ; Amir Hussain ; Huimin Zhao ; Jun Cai ; Rongjun Chen ; Yinyin Xiao ; Kaizhu Huang ; Jiangbin Zheng. 1. ed. Switzerland : Springer , 2020. pp. 550-560 (Lecture Notes in Computer Science).

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title = "Sequence similarity alignment algorithm in bioinformatics: Techniques and challenges",

abstract = "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.",

keywords = "Bioinformatics, Deoxyribonucleic acid (DNA), Longest common subsequence (LCS), Sequence alignment",

author = "Yuren Liu and Yijun Yan and Jinchang Ren and Stephen Marshall",

note = "Copyright: {\textcopyright} Springer Nature Switzerland AG 2020.; 10th International Conference on Brain Inspired Cognitive Systems, BICS 2019 ; Conference date: 13-07-2019 Through 14-07-2019",

year = "2020",

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doi = "10.1007/978-3-030-39431-8_53",

language = "English",

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series = "Lecture Notes in Computer Science",

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editor = "Jinchang Ren and Amir Hussain and Huimin Zhao and Jun Cai and Rongjun Chen and Yinyin Xiao and Kaizhu Huang and Jiangbin Zheng",

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Liu, Y, Yan, Y, Ren, J & Marshall, S 2020, Sequence similarity alignment algorithm in bioinformatics: Techniques and challenges. in J Ren, A Hussain, H Zhao, J Cai, R Chen, Y Xiao, K Huang & J Zheng (eds), Advances in Brain Inspired Cognitive Systems: 10th International Conference, BICS 2019, Guangzhou, China, July 13–14, 2019, Proceedings. 1 edn, Lecture Notes in Computer Science, vol. 11691, Springer , Switzerland, pp. 550-560, 10th International Conference on Brain Inspired Cognitive Systems, BICS 2019, Guangzhou, China, 13/07/19. https://doi.org/10.1007/978-3-030-39431-8_53

Sequence similarity alignment algorithm in bioinformatics: Techniques and challenges. / Liu, Yuren; Yan, Yijun; Ren, Jinchang (Lead / Corresponding author) et al.
Advances in Brain Inspired Cognitive Systems: 10th International Conference, BICS 2019, Guangzhou, China, July 13–14, 2019, Proceedings. ed. / Jinchang Ren; Amir Hussain; Huimin Zhao; Jun Cai; Rongjun Chen; Yinyin Xiao; Kaizhu Huang; Jiangbin Zheng. 1. ed. Switzerland: Springer , 2020. p. 550-560 (Lecture Notes in Computer Science; Vol. 11691).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Sequence similarity alignment algorithm in bioinformatics

T2 - 10th International Conference on Brain Inspired Cognitive Systems, BICS 2019

AU - Liu, Yuren

AU - Yan, Yijun

AU - Ren, Jinchang

AU - Marshall, Stephen

N1 - Copyright: © Springer Nature Switzerland AG 2020.

PY - 2020/2/1

Y1 - 2020/2/1

N2 - 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.

AB - 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.

KW - Bioinformatics

KW - Deoxyribonucleic acid (DNA)

KW - Longest common subsequence (LCS)

KW - Sequence alignment

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DO - 10.1007/978-3-030-39431-8_53

M3 - Conference contribution

AN - SCOPUS:85080962667

SN - 9783030394301

T3 - Lecture Notes in Computer Science

SP - 550

EP - 560

BT - Advances in Brain Inspired Cognitive Systems

A2 - Ren, Jinchang

A2 - Hussain, Amir

A2 - Zhao, Huimin

A2 - Cai, Jun

A2 - Chen, Rongjun

A2 - Xiao, Yinyin

A2 - Huang, Kaizhu

A2 - Zheng, Jiangbin

PB - Springer

CY - Switzerland

Y2 - 13 July 2019 through 14 July 2019

ER -

Liu Y, Yan Y, Ren J, Marshall S. Sequence similarity alignment algorithm in bioinformatics: Techniques and challenges. In Ren J, Hussain A, Zhao H, Cai J, Chen R, Xiao Y, Huang K, Zheng J, editors, Advances in Brain Inspired Cognitive Systems: 10th International Conference, BICS 2019, Guangzhou, China, July 13–14, 2019, Proceedings. 1 ed. Switzerland: Springer . 2020. p. 550-560. (Lecture Notes in Computer Science). Epub 2020 Jan 30. doi: 10.1007/978-3-030-39431-8_53

Sequence similarity alignment algorithm in bioinformatics: Techniques and challenges

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Keywords

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