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Modified Binary Inertial Particle Swarm Optimization for Gene Selection in DNA Microarray Data

  • Carlos Garibay
  • Gildardo Sanchez-AnteEmail author
  • Luis E. Falcon-Morales
  • Humberto Sossa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9116)

Abstract

DNA microarrays are being used to characterize the genetic expression of several illnesses, such as cancer. There has been interest in developing automated methods to classify the data generated by those microarrays. The problem is complex due to the availability of just a few samples to train the classifiers, and the fact that each sample may contain several thousands of features. One possibility is to select a reduced set of features (genes). In this work we propose a wrapper method that is a modified version of the Inertial Geometric Particle Swarm Optimization.We name it MIGPSO. We compare MIGPSO with other approaches. The results are promising. MIGPSO obtained an increase in accuracy of about 4 %. The number of genes selected is also competitive.

Keywords

DNA microarray PSO Feature selection Wrapper method 

Notes

Acknowledgments

The authors thank Tecnológico de Monterrey, Campus Guadalajara, as well as IPN-CIC under project SIP 20151187, and CONACYT under project 155014 for the economical support to carry out this research.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Carlos Garibay
    • 1
  • Gildardo Sanchez-Ante
    • 1
    Email author
  • Luis E. Falcon-Morales
    • 1
  • Humberto Sossa
    • 2
  1. 1.Data Visualization and Pattern Recognition LabTecnológico de Monterrey, Campus GuadalajaraZapopanMexico
  2. 2.Instituto Politécnico Nacional-Centro de Investigación En ComputaciónMéxico, D.F.México

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