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Industrial Conference on Data Mining

ICDM 2015: Advances in Data Mining: Applications and Theoretical Aspects pp 69–77Cite as

Data Mining in Pathway Analysis for Gene Expression

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9165))

Abstract

Single gene analysis looks to a single gene at a time and its relation to a specific phenotype such as cancer development. However, pathway analysis simplifies the analysis by focusing on group of genes at a time that involve in the same biological process. Pathway analysis has useful applications such as discovering diseases, diseases prevention and drug development. Different data mining approaches can be applied in pathway analysis. In this paper, we overview different pathway analysis techniques in analyzing gene expression and propose a classification for them. Pathway analysis can be classified into: detecting significant pathways and discovering new pathways. In addition, we summarize different data mining techniques that are used in pathway analysis.

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Authors and Affiliations

  1. College of Computer and Information Sciences, King Saud University, Riyadh, Kingdom of Saudi Arabia

    Amani AlAjlan & Ghada Badr

  2. IRI - The City of Scientific Research and Technological Applications, Alex, Egypt

    Ghada Badr

Authors
  1. Amani AlAjlan
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  2. Ghada Badr
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Corresponding author

Correspondence to Amani AlAjlan .

Editor information

Editors and Affiliations

  1. IBaI, Leipzig, Germany

    Petra Perner

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© 2015 Springer International Publishing Switzerland

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AlAjlan, A., Badr, G. (2015). Data Mining in Pathway Analysis for Gene Expression. In: Perner, P. (eds) Advances in Data Mining: Applications and Theoretical Aspects. ICDM 2015. Lecture Notes in Computer Science(), vol 9165. Springer, Cham. https://doi.org/10.1007/978-3-319-20910-4_6

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  • DOI: https://doi.org/10.1007/978-3-319-20910-4_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20909-8

  • Online ISBN: 978-3-319-20910-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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