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

Qufu Normal University
Anhui University

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

1 引用（Scopus）

摘要

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.

源语言	英语
主期刊名	Bioinformatics Research and Applications - 14th International Symposium, ISBRA 2018, Proceedings
编辑	Fa Zhang, Shihua Zhang, Zhipeng Cai, Pavel Skums
出版商	Springer Verlag
页	26-37
页数	12
ISBN（印刷版）	9783319949673
DOI	https://doi.org/10.1007/978-3-319-94968-0_3
出版状态	已出版 - 2018
已对外发布	是
活动	14th International Symposium on Bioinformatics Research and Applications, ISBRA 2018 - Beijing, 中国期限: 8 6月 2018 → 11 6月 2018

出版系列

姓名	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷	10847 LNBI
ISSN（印刷版）	0302-9743
ISSN（电子版）	1611-3349

会议

会议	14th International Symposium on Bioinformatics Research and Applications, ISBRA 2018
国家/地区	中国
市	Beijing
时期	8/06/18 → 11/06/18

联合国可持续发展目标

此成果有助于实现下列可持续发展目标：

可持续发展目标 3 良好健康与福祉

访问文件

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

其它文件与链接

链接到 Scopus 的出版物

引用此

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. 在 F. Zhang, S. Zhang, Z. Cai, & P. Skums (编辑), Bioinformatics Research and Applications - 14th International Symposium, ISBRA 2018, Proceedings (页码 26-37). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 10847 LNBI). Springer Verlag. https://doi.org/10.1007/978-3-319-94968-0_3

Li, Huiyu ; Li, Sheng Jun ; Shang, Junliang 等. / 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. 编辑 / Fa Zhang ; Shihua Zhang ; Zhipeng Cai ; Pavel Skums. Springer Verlag, 2018. 页码 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. 在 F Zhang, S Zhang, Z Cai & P Skums (编辑), 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), 卷 10847 LNBI, Springer Verlag, 页码 26-37, 14th International Symposium on Bioinformatics Research and Applications, ISBRA 2018, Beijing, 中国, 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 等.
Bioinformatics Research and Applications - 14th International Symposium, ISBRA 2018, Proceedings. 编辑 / Fa Zhang; Shihua Zhang; Zhipeng Cai; Pavel Skums. Springer Verlag, 2018. 页码 26-37 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 10847 LNBI).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

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. 在 Zhang F, Zhang S, Cai Z, Skums P, 编辑, Bioinformatics Research and Applications - 14th International Symposium, ISBRA 2018, Proceedings. Springer Verlag. 2018. 页码 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

摘要

出版系列

会议

联合国可持续发展目标

访问文件

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