Genomics big data hybrid depositories architecture to unlock precision medicine: a conceptual framework

  • Authors

    • Ummul H. Mohamad INSTITUTE OF VISUAL INFORMATICS, UNIVERSITI KEBANGSAAN MALAYSIA
    • Mohamad T. Ijab INSTITUTE OF VISUAL INFORMATICS, UNIVERSITI KEBANGSAAN MALAYSIA
    • Rabiah A. Kadir INSTITUTE OF VISUAL INFORMATICS, UNIVERSITI KEBANGSAAN MALAYSIA
    2018-09-24
    https://doi.org/10.14419/ijet.v7i4.16893
  • Architecture Design of Hybrid Depositories, Data Driven Genomics, Personalized Medicine Framework.

  • Abstract

    As the genome sequencing cost becomes more affordable, genomics studies are extensively carried out to empower the ultimate healthcare goal which is the precision medicine. By tailoring each individual medical treatment through precision medicine, it will potentially lead to nearly zero occurrence of the drugs side effects and treatment complications. Unfortunately, the complexity of the genomics data has been one of the bottlenecks that deter the advances of healthcare practices towards precision medicine. Therefore, based on the extensive literature review on the data driven genomics challenges towards precision medicine, this paper proposes two new contributions to the field; the conceptual framework for the genomics-based precision medicine and the architectural design for the development of hybrid depositories as the initial step to bridge the gap towards precision medicine. The genomics big data hybrid depositories architecture design is composed of few components; storage layer and service layer interconnected system such as visualization, data protection modeling, event processing engine and decision support, to carry out their purpose of merging the genomics data with the healthcare data.

     

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    H. Mohamad, U., T. Ijab, M., & A. Kadir, R. (2018). Genomics big data hybrid depositories architecture to unlock precision medicine: a conceptual framework. International Journal of Engineering & Technology, 7(4), 2585-2593. https://doi.org/10.14419/ijet.v7i4.16893

    Received date: 2018-08-05

    Accepted date: 2018-09-18

    Published date: 2018-09-24