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A rough set based rational clustering framework for determining correlated genes.

Jeba Emilyn Jeyaswamidoss1, Kesavan Thangaraj1, Kadarkarai Ramar2

  • 1Sona College of Technology , Salem, Tamilnadu, India.

Acta Microbiologica Et Immunologica Hungarica
|June 30, 2016
PubMed
Summary

This study introduces a novel biclustering algorithm using rough set theory to identify gene expression patterns. The method effectively removes irrelevant data dimensions, yielding meaningful gene clusters with overlapping capabilities.

Keywords:
biclustering algorithmcorrelation clusteringgene expression dataoverlapping biclustersrough clustering

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Cluster analysis is crucial for identifying co-regulated genes in high-dimensional gene expression data.
  • Existing algorithms face challenges with irrelevant dimensions and rigid cluster assignments.

Purpose of the Study:

  • To develop an intelligent rough clustering technique for efficient dimension reduction and meaningful cluster identification.
  • To propose a novel biclustering algorithm based on rough set theory for gene expression analysis.

Main Methods:

  • Utilized rough set theory for biclustering gene expression data.
  • Employed correlation coefficient for simultaneous row and column clustering.
  • Applied mean squared residue for initial bicluster generation and refinement of gene membership.

Main Results:

  • Successfully removed irrelevant dimensions from high-dimensional gene expression data.
  • Generated meaningful biclusters with clear lower and upper boundaries.
  • Demonstrated the effectiveness of the algorithm on yeast gene expression data.

Conclusions:

  • The proposed rough set-based biclustering technique offers an effective approach for gene expression analysis.
  • The method overcomes limitations of initial cluster selection and allows for overlapping biclusters.
  • This technique enhances the identification of complex gene behaviors and relationships.