About | Contact Us | Register | Login
ProceedingsSeriesJournalsSearchEAI
Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part I

Research Article

Research on Big Data Classification Algorithm of Disease Gene Detection Based on Complex Network Technology

Download(Requires a free EAI acccount)
3 downloads
Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-030-67871-5_28,
        author={Yuan-yuan Gao and Ju Xiang and Yan-ni Tang and Miao He and Wang Li},
        title={Research on Big Data Classification Algorithm of Disease Gene Detection Based on Complex Network Technology},
        proceedings={Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part I},
        proceedings_a={ADHIP},
        year={2021},
        month={2},
        keywords={Complex network technology Disease genes Big data Classification algorithm},
        doi={10.1007/978-3-030-67871-5_28}
    }
    
  • Yuan-yuan Gao
    Ju Xiang
    Yan-ni Tang
    Miao He
    Wang Li
    Year: 2021
    Research on Big Data Classification Algorithm of Disease Gene Detection Based on Complex Network Technology
    ADHIP
    Springer
    DOI: 10.1007/978-3-030-67871-5_28
Yuan-yuan Gao1, Ju Xiang1, Yan-ni Tang1, Miao He1, Wang Li2
  • 1: Changsha Medical College
  • 2: College of Big Data, TongRen University

Abstract

In order to improve the accuracy of the classification of the big data of disease gene detection, an algorithm for the classification of the big data of disease gene detection based on the complex network technology was proposed. On the basis of complex network technology, a distance-based membership function is first established. Considering the distance between the sample and the class center, the membership function of sample compactness is designed to complete the establishment of membership function of complex network. Combined with the design of the classification algorithm flow of the big data of disease gene detection, the design of the data classification algorithm was completed, and the classification of the big data of disease gene detection was realized. The experimental results show that the proposed algorithm is more accurate than the other two classification algorithms in the big data sets of different disease genes.

Keywords
Complex network technology Disease genes Big data Classification algorithm
Published
2021-02-03
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-67871-5_28
Copyright © 2020–2025 ICST
EBSCOProQuestDBLPDOAJPortico
EAI Logo

About EAI

  • Who We Are
  • Leadership
  • Research Areas
  • Partners
  • Media Center

Community

  • Membership
  • Conference
  • Recognition
  • Sponsor Us

Publish with EAI

  • Publishing
  • Journals
  • Proceedings
  • Books
  • EUDL