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TASB-AC: Term Annotated Sliding-Window-Based Boosting Associative Classifier for DNA Repair Gene Categorization

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Proceedings of International Symposium on Sensor Networks, Systems and Security (ISSNSS 2017)

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Abstract

Damage to DNA affects the biochemical pathways of the cell and leads to aging, if not repaired. Several genes in the genome of an organism are responsible for DNA repair activities, however, not all of them are related to the biological aging process. In this paper, we develop a data mining technique to relate association of DNA repair genes with the aging process of the organism. Nucleotide sequence of the DNA repair genes is annotated with their respective biochemical properties and is then converted to a transactional dataset. Further, biological features are extracted from the dataset by constructing an associative classifier. To select significant gene features, we employ sliding-window technique to divide the gene sequence into subsequences and thus increase their count. An extensive evaluation is performed of the proposed technique by taking human DNA repair genes along with their biochemical properties like gene ontology terms and protein–protein interactions. We also provide biological interpretation of the features extracted from the classification technique.

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Notes

  1. 1.

    http://bioperl.org/.

  2. 2.

    http://www.geneontology.org/.

  3. 3.

    https://bioconductor.org/packages/release/bioc/html/biomaRt.html.

  4. 4.

    http://www.hprd.org/.

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Author information

Authors and Affiliations

  1. Department of Information Science and Engineering, Vivekananda Institute of Technology, Bangalore, India

    A. Vidya

  2. Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore University, Bangalore, India

    Santosh Pattar, M. S. Roopa & K. R. Venugopal

  3. Department of Computer Science and Automation, Indian Institute of Science, Bangalore, India

    L. M. Patnaik

Authors
  1. A. Vidya
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  2. Santosh Pattar
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  3. M. S. Roopa
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  4. K. R. Venugopal
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  5. L. M. Patnaik
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Editor information

Editors and Affiliations

  1. Computer Science & Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA

    Nageswara S.V. Rao

  2. Clemson University, Clemson, South Carolina, USA

    Richard R. Brooks

  3. Department of Computer Science, New Jersey Institute of Technology, Newark, New Jersey, USA

    Chase Q. Wu

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Vidya, A., Pattar, S., Roopa, M.S., Venugopal, K.R., Patnaik, L.M. (2018). TASB-AC: Term Annotated Sliding-Window-Based Boosting Associative Classifier for DNA Repair Gene Categorization. In: Rao, N., Brooks, R., Wu, C. (eds) Proceedings of International Symposium on Sensor Networks, Systems and Security. ISSNSS 2017. Springer, Cham. https://doi.org/10.1007/978-3-319-75683-7_19

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  • DOI: https://doi.org/10.1007/978-3-319-75683-7_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75682-0

  • Online ISBN: 978-3-319-75683-7

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