An improved particle swarm optimization with dynamic scale-free network for detecting multi-omics features

Huiyu Li; Sheng Jun Li; Junliang Shang; Jin Xing Liu; Chun Hou Zheng

doi:10.1007/978-3-319-94968-0_3

An improved particle swarm optimization with dynamic scale-free network for detecting multi-omics features

Huiyu Li
, Sheng Jun Li
, Junliang Shang
, Jin Xing Liu
, Chun Hou Zheng

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

1 Scopus citations

Abstract

Along with the rapid development of high-throughput sequencing technology, a large amount of multi-omics data sets are generated, which provide more opportunities to understand the mechanism of complex diseases. In this study, an improved particle swarm optimization with dynamic scale-free network, named DSFPSO, is proposed for detecting multi-omics features. The highlights of DSFPSO are the introduced scale-free network and velocity updating strategies. The scale-free network is employed to DSFPSO as its population structure, which can dynamically adjust the iteration processes. Three types of velocity updating strategies are used in DSFPSO for fully considering the heterogeneity of particles and their neighbors. Both gene function analysis and pathway analysis on colorectal cancer (CRC) data show that DSFPSO can detect CRC-associated features effectively.

Original language	English
Title of host publication	Bioinformatics Research and Applications - 14th International Symposium, ISBRA 2018, Proceedings
Editors	Fa Zhang, Shihua Zhang, Zhipeng Cai, Pavel Skums
Publisher	Springer Verlag
Pages	26-37
Number of pages	12
ISBN (Print)	9783319949673
DOIs	https://doi.org/10.1007/978-3-319-94968-0_3
State	Published - 2018
Externally published	Yes
Event	14th International Symposium on Bioinformatics Research and Applications, ISBRA 2018 - Beijing, China Duration: 8 Jun 2018 → 11 Jun 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10847 LNBI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	14th International Symposium on Bioinformatics Research and Applications, ISBRA 2018
Country/Territory	China
City	Beijing
Period	8/06/18 → 11/06/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Colorectal cancer
Dynamic scale-free network
Multi-omics
Mutual information
Particle swarm optimization

Access to Document

10.1007/978-3-319-94968-0_3

Cite this

Li, H., Li, S. J., Shang, J., Liu, J. X., & Zheng, C. H. (2018). An improved particle swarm optimization with dynamic scale-free network for detecting multi-omics features. In F. Zhang, S. Zhang, Z. Cai, & P. Skums (Eds.), Bioinformatics Research and Applications - 14th International Symposium, ISBRA 2018, Proceedings (pp. 26-37). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10847 LNBI). Springer Verlag. https://doi.org/10.1007/978-3-319-94968-0_3

Li, Huiyu ; Li, Sheng Jun ; Shang, Junliang et al. / An improved particle swarm optimization with dynamic scale-free network for detecting multi-omics features. Bioinformatics Research and Applications - 14th International Symposium, ISBRA 2018, Proceedings. editor / Fa Zhang ; Shihua Zhang ; Zhipeng Cai ; Pavel Skums. Springer Verlag, 2018. pp. 26-37 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{a6efdc362c2542b1af5d74af6e669bc9,

title = "An improved particle swarm optimization with dynamic scale-free network for detecting multi-omics features",

abstract = "Along with the rapid development of high-throughput sequencing technology, a large amount of multi-omics data sets are generated, which provide more opportunities to understand the mechanism of complex diseases. In this study, an improved particle swarm optimization with dynamic scale-free network, named DSFPSO, is proposed for detecting multi-omics features. The highlights of DSFPSO are the introduced scale-free network and velocity updating strategies. The scale-free network is employed to DSFPSO as its population structure, which can dynamically adjust the iteration processes. Three types of velocity updating strategies are used in DSFPSO for fully considering the heterogeneity of particles and their neighbors. Both gene function analysis and pathway analysis on colorectal cancer (CRC) data show that DSFPSO can detect CRC-associated features effectively.",

keywords = "Colorectal cancer, Dynamic scale-free network, Multi-omics, Mutual information, Particle swarm optimization",

author = "Huiyu Li and Li, \{Sheng Jun\} and Junliang Shang and Liu, \{Jin Xing\} and Zheng, \{Chun Hou\}",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; 14th International Symposium on Bioinformatics Research and Applications, ISBRA 2018 ; Conference date: 08-06-2018 Through 11-06-2018",

year = "2018",

doi = "10.1007/978-3-319-94968-0\_3",

language = "英语",

isbn = "9783319949673",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "26--37",

editor = "Fa Zhang and Shihua Zhang and Zhipeng Cai and Pavel Skums",

booktitle = "Bioinformatics Research and Applications - 14th International Symposium, ISBRA 2018, Proceedings",

}

Li, H, Li, SJ, Shang, J, Liu, JX & Zheng, CH 2018, An improved particle swarm optimization with dynamic scale-free network for detecting multi-omics features. in F Zhang, S Zhang, Z Cai & P Skums (eds), Bioinformatics Research and Applications - 14th International Symposium, ISBRA 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10847 LNBI, Springer Verlag, pp. 26-37, 14th International Symposium on Bioinformatics Research and Applications, ISBRA 2018, Beijing, China, 8/06/18. https://doi.org/10.1007/978-3-319-94968-0_3

An improved particle swarm optimization with dynamic scale-free network for detecting multi-omics features. / Li, Huiyu; Li, Sheng Jun; Shang, Junliang et al.
Bioinformatics Research and Applications - 14th International Symposium, ISBRA 2018, Proceedings. ed. / Fa Zhang; Shihua Zhang; Zhipeng Cai; Pavel Skums. Springer Verlag, 2018. p. 26-37 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10847 LNBI).

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

TY - GEN

T1 - An improved particle swarm optimization with dynamic scale-free network for detecting multi-omics features

AU - Li, Huiyu

AU - Li, Sheng Jun

AU - Shang, Junliang

AU - Liu, Jin Xing

AU - Zheng, Chun Hou

N1 - Publisher Copyright: © Springer International Publishing AG, part of Springer Nature 2018.

PY - 2018

Y1 - 2018

N2 - Along with the rapid development of high-throughput sequencing technology, a large amount of multi-omics data sets are generated, which provide more opportunities to understand the mechanism of complex diseases. In this study, an improved particle swarm optimization with dynamic scale-free network, named DSFPSO, is proposed for detecting multi-omics features. The highlights of DSFPSO are the introduced scale-free network and velocity updating strategies. The scale-free network is employed to DSFPSO as its population structure, which can dynamically adjust the iteration processes. Three types of velocity updating strategies are used in DSFPSO for fully considering the heterogeneity of particles and their neighbors. Both gene function analysis and pathway analysis on colorectal cancer (CRC) data show that DSFPSO can detect CRC-associated features effectively.

AB - Along with the rapid development of high-throughput sequencing technology, a large amount of multi-omics data sets are generated, which provide more opportunities to understand the mechanism of complex diseases. In this study, an improved particle swarm optimization with dynamic scale-free network, named DSFPSO, is proposed for detecting multi-omics features. The highlights of DSFPSO are the introduced scale-free network and velocity updating strategies. The scale-free network is employed to DSFPSO as its population structure, which can dynamically adjust the iteration processes. Three types of velocity updating strategies are used in DSFPSO for fully considering the heterogeneity of particles and their neighbors. Both gene function analysis and pathway analysis on colorectal cancer (CRC) data show that DSFPSO can detect CRC-associated features effectively.

KW - Colorectal cancer

KW - Dynamic scale-free network

KW - Multi-omics

KW - Mutual information

KW - Particle swarm optimization

UR - https://www.scopus.com/pages/publications/85050359267

U2 - 10.1007/978-3-319-94968-0_3

DO - 10.1007/978-3-319-94968-0_3

M3 - 会议稿件

AN - SCOPUS:85050359267

SN - 9783319949673

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 26

EP - 37

BT - Bioinformatics Research and Applications - 14th International Symposium, ISBRA 2018, Proceedings

A2 - Zhang, Fa

A2 - Zhang, Shihua

A2 - Cai, Zhipeng

A2 - Skums, Pavel

PB - Springer Verlag

T2 - 14th International Symposium on Bioinformatics Research and Applications, ISBRA 2018

Y2 - 8 June 2018 through 11 June 2018

ER -

Li H, Li SJ, Shang J, Liu JX, Zheng CH. An improved particle swarm optimization with dynamic scale-free network for detecting multi-omics features. In Zhang F, Zhang S, Cai Z, Skums P, editors, Bioinformatics Research and Applications - 14th International Symposium, ISBRA 2018, Proceedings. Springer Verlag. 2018. p. 26-37. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-94968-0_3

An improved particle swarm optimization with dynamic scale-free network for detecting multi-omics features

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this