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Gene Expression Analysis Using Clustering Methods: Comparison Analysis

  • K. SathishkumarEmail author
  • E. Balamurugan
  • Jackson Akpojoro
  • M. Ramalingam
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 39)

Abstract

A microarray measures the articulation dimensions of thousands of qualities. Meanwhile, Grouping examines microarray quality articulation information. In this paper, have executed a biclustering calculation to distinguish subgroups of information which shows corresponded conduct under explicit test conditions. During the time spent for discovering bi-clusters, Fuzzy K-implies grouping is utilized to bunch the qualities and tests with most extreme enrolment work. Both dimensionality and lessening the quality shaving are finished utilizing LFDA and quality sifting with the capacity separately. From the outcomes it presumes that the proposed work performs better when contrasted with other existing bunching calculations, for example, FCM, FPCM and EMFPCM.

Keywords

Clustering Fuzzy K means Classification Cancer data LFDA 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • K. Sathishkumar
    • 1
    Email author
  • E. Balamurugan
    • 1
  • Jackson Akpojoro
    • 1
  • M. Ramalingam
    • 2
  1. 1.University of Africa, Toru-OruaBayelsaNigeria
  2. 2.Gobi Arts and Science CollegeGobiIndia

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