An Improved Particle Swarm Optimization with Dynamic Scale-Free Network for Detecting Multi-omics Features

  • Huiyu Li
  • Sheng-Jun LiEmail author
  • Junliang ShangEmail author
  • Jin-Xing Liu
  • Chun-Hou Zheng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10847)


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.


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



This work was supported by the National Natural Science Foundation of China (Grant No. 61502272, 61572284); Project of Shandong Province Higher Educational Science and Technology Program (J18KA373); the Scientific Research Foundation of Qufu Normal University (BSQD20130119); the Science and Technology Planning Project of Qufu Normal University (xkj201524).

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Information Science and EngineeringQufu Normal UniversityRizhaoChina
  2. 2.School of StatisticsQufu Normal UniversityQufuChina
  3. 3.School of Computer Science and TechnologyAnhui UniversityHefeiChina

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