Cloud-Based Genomic Data Analysis: IT-enabled Solutions for Biotechnology Advancements

Authors

  • Arun Kumar Sandu Lead Engineer – Databases, Grab Technology, 777 108th Ave NE Unit 1900, Bellevue, WA 98004, USA
  • Rajani Pydipalli Statistical Programmer, Gilead Sciences Inc., Foster City, California, USA
  • Jayadip GhanshyamBhai Tejani Industrial Chemist, National Rubber Corporation, Canonsburg, PA, USA
  • Sai Sirisha Maddula Front End Developer, Delta Airlines, Atlanta, Georgia, United States
  • Marcus Rodriguez Princeton Institute for Computational Science and Engineering (PICSciE), Princeton University, NJ, USA

DOI:

https://doi.org/10.18034/ei.v10i2.712

Keywords:

Cloud Computing, Genomic Data, Data Analysis, Biotechnology, IT Solutions, Bioinformatics, Cloud-Based Systems, Genomics Technology

Abstract

This study explores how cloud-based genetic data analysis can advance biotechnology in a revolutionary way. The primary goals are to investigate how cloud computing and genetic analysis might be integrated, assess system performance using case studies and performance measures, and look at potential future directions and policy consequences. Methodologically, reports, case studies, and current literature were synthesized using a secondary data-based review approach. Important discoveries demonstrate how cloud-based systems can improve genomic research's scalability, efficiency, and collaboration. However, issues to be resolved, such as the digital gap, ethical governance, and data privacy, are also important. The consequences of policy highlight the necessity of solid frameworks to protect personal information, close the digital gap, and advance moral research methods. Cloud-based genomic data analysis presents opportunities for biotechnology advancements and discoveries to be made faster. Still, it raises ethical, legal, and policy questions that must be carefully considered.

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Published

2022-10-20

Issue

Section

Peer Reviewed Articles

How to Cite

Sandu, A. K., Pydipalli, R., Tejani, J. G., Maddula, S. S., & Rodriguez, M. (2022). Cloud-Based Genomic Data Analysis: IT-enabled Solutions for Biotechnology Advancements. Engineering International, 10(2), 103-116. https://doi.org/10.18034/ei.v10i2.712

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