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Sorting Out Non-Synonymous Single Nucleotide Polymorphism Leads to Novel Biomarker Discovery for Disease Prognosis

Author

Listed:
  • Mohammad Uzzal Hossain

    (Bioinformatics Division, National Institute of Biotechnology, Ganakbari, Ashulia, Savar, Dhaka-1349, Bangladesh)

  • Keshob Chandra Das
  • U.S. Mahzabin Amin
  • Md. Salimullah

    (Bioinformatics Division, National Institute of Biotechnology, Ganakbari, Ashulia, Savar, Dhaka-1349, Bangladesh)

  • Chaman Ara Keya

    (Department of Biochemistry and Microbiology, North South University, Bashundhara , Dhaka-1229, Bangladesh)

Abstract

Hereditary genetic variation which is considered to be primarily caused by single nucleotide polymorphism (SNP), is a significant drawback for developing universal therapy against diseases. Among others, non-synonymous SNP (nsSNP) could be fatal due to its effect on structure and function of the ultimate gene product. Therefore, study of functional nsSNP’s would provide an insight into the exact cause underlying the onset of genetic variation and possible methodologies for the cure or early management of the disease. Various in silico tools could be employed to screen and map the deleterious nsSNP’s to the protein structure for predicting the structure-function effects. Further, these nsSNPs upon experimental verification would be ideal candidate for the disease risk assessment. Positive linkage study would enforce novel biomarker discovery for specific disease prognosis.

Suggested Citation

  • Mohammad Uzzal Hossain & Keshob Chandra Das & U.S. Mahzabin Amin & Md. Salimullah & Chaman Ara Keya, 2017. "Sorting Out Non-Synonymous Single Nucleotide Polymorphism Leads to Novel Biomarker Discovery for Disease Prognosis," Current Trends in Biomedical Engineering & Biosciences, Juniper Publishers Inc., vol. 3(2), pages 27-30, April.
    • Handle: RePEc:adp:jctbeb:v:3:y:2017:i:2:p:27-30
    DOI: 10.19080/CTBEB.2017.03.555608
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