K-mer Counting: Memory-efficient strategy, parallel computing and field of application for Bioinformatics

Ming Xiao; Jiakun Li; Song Hong; Yongtao Yang; Junhua Li; Jianxin Wang; Jian Yang; Wenbiao Ding; Le Zhang

doi:10.1109/BIBM.2018.8621325

K-mer Counting: Memory-efficient strategy, parallel computing and field of application for Bioinformatics

Ming Xiao, Jiakun Li, Song Hong, Yongtao Yang, Junhua Li, Jianxin Wang, Jian Yang, Wenbiao Ding, Le Zhang^*

^*Corresponding author for this work

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

6 Citations (Scopus)

Abstract

Currently, k-mer counting is an important algorithm for bioinformatics research. This review lists the major application fields of k-mer counting in Bioinformatics at the beginning. Next, we introduce the commonly used memory-efficient strategy for k-mer counting tools, because the large amount of memory request is a bottleneck of k-mer counting tools. Next we illustrate the current parallel computing technologies for k-mer counting tool. Finally, we discuss the future study for k-mer counting.

Original language	English
Title of host publication	Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
Editors	Harald Schmidt, David Griol, Haiying Wang, Jan Baumbach, Huiru Zheng, Zoraida Callejas, Xiaohua Hu, Julie Dickerson, Le Zhang
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2561-2567
Number of pages	7
ISBN (Electronic)	9781538654880
DOIs	https://doi.org/10.1109/BIBM.2018.8621325
Publication status	Published - 21 Jan 2019
Event	2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 - Madrid, Spain Duration: 3 Dec 2018 → 6 Dec 2018

Publication series

Name	Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018

Conference

Conference	2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
Country/Territory	Spain
City	Madrid
Period	3/12/18 → 6/12/18

Keywords

Bioinformatics
genome sequence analysis
k-mer counting

Access to Document

10.1109/BIBM.2018.8621325

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Xiao, M., Li, J., Hong, S., Yang, Y., Li, J., Wang, J., Yang, J., Ding, W., & Zhang, L. (2019). K-mer Counting: Memory-efficient strategy, parallel computing and field of application for Bioinformatics. In H. Schmidt, D. Griol, H. Wang, J. Baumbach, H. Zheng, Z. Callejas, X. Hu, J. Dickerson, & L. Zhang (Eds.), Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 (pp. 2561-2567). Article 8621325 (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2018.8621325

Xiao, Ming ; Li, Jiakun ; Hong, Song et al. / K-mer Counting : Memory-efficient strategy, parallel computing and field of application for Bioinformatics. Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. editor / Harald Schmidt ; David Griol ; Haiying Wang ; Jan Baumbach ; Huiru Zheng ; Zoraida Callejas ; Xiaohua Hu ; Julie Dickerson ; Le Zhang. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 2561-2567 (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018).

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title = "K-mer Counting: Memory-efficient strategy, parallel computing and field of application for Bioinformatics",

abstract = "Currently, k-mer counting is an important algorithm for bioinformatics research. This review lists the major application fields of k-mer counting in Bioinformatics at the beginning. Next, we introduce the commonly used memory-efficient strategy for k-mer counting tools, because the large amount of memory request is a bottleneck of k-mer counting tools. Next we illustrate the current parallel computing technologies for k-mer counting tool. Finally, we discuss the future study for k-mer counting.",

keywords = "Bioinformatics, genome sequence analysis, k-mer counting",

author = "Ming Xiao and Jiakun Li and Song Hong and Yongtao Yang and Junhua Li and Jianxin Wang and Jian Yang and Wenbiao Ding and Le Zhang",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 ; Conference date: 03-12-2018 Through 06-12-2018",

year = "2019",

month = jan,

day = "21",

doi = "10.1109/BIBM.2018.8621325",

language = "English",

series = "Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018",

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editor = "Harald Schmidt and David Griol and Haiying Wang and Jan Baumbach and Huiru Zheng and Zoraida Callejas and Xiaohua Hu and Julie Dickerson and Le Zhang",

booktitle = "Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018",

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Xiao, M, Li, J, Hong, S, Yang, Y, Li, J, Wang, J, Yang, J, Ding, W & Zhang, L 2019, K-mer Counting: Memory-efficient strategy, parallel computing and field of application for Bioinformatics. in H Schmidt, D Griol, H Wang, J Baumbach, H Zheng, Z Callejas, X Hu, J Dickerson & L Zhang (eds), Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018., 8621325, Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018, Institute of Electrical and Electronics Engineers Inc., pp. 2561-2567, 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018, Madrid, Spain, 3/12/18. https://doi.org/10.1109/BIBM.2018.8621325

K-mer Counting: Memory-efficient strategy, parallel computing and field of application for Bioinformatics. / Xiao, Ming; Li, Jiakun; Hong, Song et al.
Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. ed. / Harald Schmidt; David Griol; Haiying Wang; Jan Baumbach; Huiru Zheng; Zoraida Callejas; Xiaohua Hu; Julie Dickerson; Le Zhang. Institute of Electrical and Electronics Engineers Inc., 2019. p. 2561-2567 8621325 (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018).

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

TY - GEN

T1 - K-mer Counting

T2 - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018

AU - Xiao, Ming

AU - Li, Jiakun

AU - Hong, Song

AU - Yang, Yongtao

AU - Li, Junhua

AU - Wang, Jianxin

AU - Yang, Jian

AU - Ding, Wenbiao

AU - Zhang, Le

PY - 2019/1/21

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N2 - Currently, k-mer counting is an important algorithm for bioinformatics research. This review lists the major application fields of k-mer counting in Bioinformatics at the beginning. Next, we introduce the commonly used memory-efficient strategy for k-mer counting tools, because the large amount of memory request is a bottleneck of k-mer counting tools. Next we illustrate the current parallel computing technologies for k-mer counting tool. Finally, we discuss the future study for k-mer counting.

AB - Currently, k-mer counting is an important algorithm for bioinformatics research. This review lists the major application fields of k-mer counting in Bioinformatics at the beginning. Next, we introduce the commonly used memory-efficient strategy for k-mer counting tools, because the large amount of memory request is a bottleneck of k-mer counting tools. Next we illustrate the current parallel computing technologies for k-mer counting tool. Finally, we discuss the future study for k-mer counting.

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KW - genome sequence analysis

KW - k-mer counting

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M3 - Conference contribution

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SP - 2561

EP - 2567

BT - Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018

A2 - Schmidt, Harald

A2 - Griol, David

A2 - Wang, Haiying

A2 - Baumbach, Jan

A2 - Zheng, Huiru

A2 - Callejas, Zoraida

A2 - Hu, Xiaohua

A2 - Dickerson, Julie

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PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 3 December 2018 through 6 December 2018

ER -

Xiao M, Li J, Hong S, Yang Y, Li J, Wang J et al. K-mer Counting: Memory-efficient strategy, parallel computing and field of application for Bioinformatics. In Schmidt H, Griol D, Wang H, Baumbach J, Zheng H, Callejas Z, Hu X, Dickerson J, Zhang L, editors, Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. Institute of Electrical and Electronics Engineers Inc. 2019. p. 2561-2567. 8621325. (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018). doi: 10.1109/BIBM.2018.8621325

K-mer Counting: Memory-efficient strategy, parallel computing and field of application for Bioinformatics

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