International Journal of Current Microbiology and Applied Sciences (IJCMAS)
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Original Research Articles                      Volume : 9, Issue:12, December, 2020

PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
Publisher : Excellent Publishers
Email : /
Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2018: 95.39
NAAS RATING 2020: 5.38

Int.J.Curr.Microbiol.App.Sci.2020.9(12): 592-598

The Germ Theory of COVID-19 Pandemic and Similarity Analysis of Genomics – A Machine Learning Approach
K.M. Shivakumar1, M. Kalpana2* and C. S. Sumathi2
1Faculty of Agricultural Economics, Centre for Agricultural and Rural Development Studies, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India,
2Faculty of Computer Science, Anbil Dharmalingam Agricultural College and Research Institute, Tiruchirappalli, Tamil Nadu, India
*Corresponding author

The COVID - 19 pandemic creates havoc all around the world for human beings impacting their health, livelihood, employment, processing, economy etc. All the countries take various efforts like social distancing, containment, self- quarantine, severe testing but the spread of virus is taken place at an alarming rate. This article just provides the scenario of spread of pandemic COVID 19 in the most affected top 10 countries and also provides the similarity analysis of the RNA sequence of the virus affected victims in some of these countries to help them the causal agent and their genetic makeup in taking up preventive and quarantine measures.

Keywords: COVID-19, Spread of infections, Doubling Time, RNA Similarity Analysis

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How to cite this article:

Shivakumar, K. M., M. Kalpana and Sumathi, C. S. 2020. The Germ Theory of COVID-19 Pandemic and Similarity Analysis of Genomics – A Machine Learning Approach.Int.J.Curr.Microbiol.App.Sci. 9(12): 592-598. doi:
Copyright: This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike license.