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Gene-Gene Interaction Analysis: Correlation, Relative Entropy and Rough Set Theory Based Approach

  • Sujay SahaEmail author
  • Sukriti Roy
  • Anupam Ghosh
  • Kashi Nath Dey
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10814)

Abstract

Logical interaction between every pair of genes in a gene interaction network affects the observable behavior of any organism. This genetic interaction helps us to identify pathways of associated genes for various diseases and also finds the level of interaction between the genes in the network. In this paper, at first we have used three correlation measures, like Pearson, Spearman and Kendall-Tau to find the interaction level in a gene interaction network. Rough set can also be used to find the level of interaction, as well as direction of interaction between every pair of genes. That’s why in the second phase of the experiment, entropy measure & Rough set theory are also used to determine the level of interaction between every pair of genes as well as finds the direction of interaction that indicates which gene regulates which other genes. Experiments are done on normal & diseased samples of Colorectal Cancer dataset (GDS4382) separately. At the end we try to find out those interactions responsible for this cancer disease to take place. To validate the experimental results biologically we compare it with interactions given in NCBI database.

Keywords

Gene – gene interaction Correlation Entropy Rough sets DNA microarray Colorectal cancer 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.CSE DepartmentHeritage Institute of TechnologyKolkataIndia
  2. 2.CSE DepartmentNetaji Subhash Engineering CollegeKolkataIndia
  3. 3.CSE DepartmentUniversity of CalcuttaKolkataIndia

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