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A Hybrid of SVM and SCAD with Group-Specific Tuning Parameter for Pathway-Based Microarray Analysis

  • Muhammad Faiz Misman
  • Mohd Saberi Mohamad
  • Safaai Deris
  • Raja Nurul Mardhiah Raja Mohamad
  • Siti Zaiton Mohd Hashim
  • Sigeru Omatu
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 151)

Abstract

The incorporation of pathway data into the microarray analysis had lead to a new era in advance understanding of biological processes. However, this advancement is limited by the two issues in quality of pathway data. First, the pathway data are usually made from the biological context free, when it comes to a specific cellular process (e.g. lung cancer development), it can be that only several genes within pathways are responsible for the corresponding cellular process. Second, pathway data commonly curated from the literatures, it can be that some pathway may be included with the uninformative genes while the informative genes may be excluded. In this paper, we proposed a hybrid of support vector machine and smoothly clipped absolute deviation with group-specific tuning parameters (gSVM-SCAD) to select informative genes within pathways before the pathway evaluation process. Our experiments on lung cancer and gender data sets show that gSVM-SCAD obtains significant results in classification accuracy and in selecting the informative genes and pathways.

Keywords

Support Vector Machine Linear Discriminant Analysis Penalty Function Feature Selection Method Reproduce Kernel Hilbert Space 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Muhammad Faiz Misman
    • 1
  • Mohd Saberi Mohamad
    • 1
  • Safaai Deris
    • 1
  • Raja Nurul Mardhiah Raja Mohamad
    • 1
  • Siti Zaiton Mohd Hashim
    • 2
  • Sigeru Omatu
    • 3
  1. 1.Artificial Intelligence & Bioinformatics Research Group, Faculty of Computer Science and Information SystemsUniversiti Teknologi MalaysiaSkudaiMalaysia
  2. 2.Soft Computing Research Group, Faculty of Computer Science and Information SystemsUniversiti Teknologi MalaysiaSkudaiMalaysia
  3. 3.Department of Electronics, Information and Communication EngineeringOsaka Institute of TechnologyOsakaJapan

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