Spectral domain characterization of genome sequences

  • Authors

    • P Venkateswarlu
    • E G. Rajan
    2018-04-03
    https://doi.org/10.14419/ijet.v7i2.12.11277
  • Genome Sequence, Spectral Characterization, Big Data, Map Reduce

  • Abstract

    Genome sequencing became an important research area for understanding order of DNA and discovering genetic secrets of humans. Fortunately voluminous data in this area is available for the study of genome sequences. Characterization of genome sequences is non-trivial and tedious task. Nevertheless, algorithms were found in the literature to study them. As the genome sequences data has characteristics of big data we proposed a technique based on MapReduce programming paradigm to attempt spectral characterization of genome sequences. A machine learning approach is used to discover trends in the genome sequences. Rationale behind using MapReduce, a distributed programming framework, is its support for parallel processing and the usage of more powerful Graphical Processing Units (GPUs). Moreover, the datasets can be maintained in cloud so as to handle it with ease. We built a prototype application to demonstrate proof of the concept. Our empirical results reveal encouraging observations in the genomic study.

     

     

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  • How to Cite

    Venkateswarlu, P., & G. Rajan, E. (2018). Spectral domain characterization of genome sequences. International Journal of Engineering & Technology, 7(2.12), 189-192. https://doi.org/10.14419/ijet.v7i2.12.11277

    Received date: 2018-04-08

    Accepted date: 2018-04-08

    Published date: 2018-04-03