Ensemble Classification of Cancer Types and Biomarker Identification

Authors

  • Hussein Hijazi,

    1. Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA
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  • Ming Wu,

    1. Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA
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  • Aritro Nath,

    1. Genetics Program, Michigan State University, East Lansing, MI, USA
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  • Christina Chan

    Corresponding author
    1. Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA
    2. Genetics Program, Michigan State University, East Lansing, MI, USA
    3. Department of Chemical Engineering and Material Science, Michigan State University, East Lansing, MI, USA
    • Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA
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Correspondence to: Christina Chan, Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA.

E-mail: krischan@egr.msu.edu

Abstract

Preclinical Research

Cancer classification is an important step in biomarker identification. Developing machine learning methods that correctly predict cancer subtypes/types can help in identifying potential cancer biomarkers. In this commentary, we presented ensemble classification approach and compared its performance with single classification approaches. Additionally, the application of cancer classification in identifying biomarkers for drug design was discussed.

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