A Fuzzy Model for Gene Expression Profiles Reducing Based on the Complex Use of Statistical Criteria and Shannon Entropy

  • Sergii Babichev
  • Volodymyr Lytvynenko
  • Aleksandr Gozhyj
  • Maksym Korobchynskyi
  • Mariia Voronenko
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 754)

Abstract

The paper presents the technology of gene expression profiles reducing based on the complex use of fuzzy logic methods, statistical criteria and Shannon entropy. Simulation of the reducing process has been performed with the use of gene expression profiles of lung cancer patients. The variance and the average absolute value were changed within the defined range from the minimum to the maximum value, and Shannon entropy from the maximum to the minimum value during the simulation process. 311 gene expression profiles from 7129 were removed as non-informativity during simulation process. The structural block diagram of the step-by-step data processing in order to remove non-informativity gene expression profiles has been proposed as the simulation results.

Keywords

Fuzzy logic Gene expression profiles Reducing Statistical criteria Shannon entropy 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Sergii Babichev
    • 1
    • 2
  • Volodymyr Lytvynenko
    • 1
  • Aleksandr Gozhyj
    • 3
  • Maksym Korobchynskyi
    • 4
  • Mariia Voronenko
    • 1
  1. 1.Kherson National Technical UniversityKhersonUkraine
  2. 2.Jan Evangelista Purkyne University in Usti nad LabemUsti nad LabemCzech Republic
  3. 3.Petro Mohyla Black Sea National UniversityNikolaevUkraine
  4. 4.Military-Diplomatic Academy named Eugene BereznyakKievUkraine

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