Cluster Analysis of COVID-19 Through Genome Sequences Using Python Bioinformatics Library

Maryam Ghauri; Naeem Ahmed Mahoto; Sania Bhatti; Aqsa Umar

Authors

Maryam Ghauri Department of Software Engineering, Mehran University of Engineering & Technology Jamshoro, Pakistan.
Naeem A. Mahoto Department of Software Engineering, Mehran University of Engineering & Technology Jamshoro, Pakistan.
Sania Bhatti Department of Software Engineering, Mehran University of Engineering & Technology Jamshoro, Pakistan.
Aqsa Umar Department of Software Engineering, Mehran University of Engineering & Technology Jamshoro, Pakistan.

Keywords:

Covid-19, Genome sequences, nucleotide records, biomedical, python

Abstract

Introduction and Importance of Study:

During the COVID-19 pandemic, mortality rates varied across different regions of the world. To better understand the virus's behavior, it's important to gain in-depth knowledge of the nucleotide records of the COVID-19 genomic sequence.

Novelty Statement:

In the study, researchers analyzed clusters of highly affected countries to find similar codons in countries with a similar effect of the virus through Python based library.

Material And Method:

Nucleotide records were extracted from the NCBI database in FASTA format. Further Python Bioinformatics library was used to form the clusters of each country using the K-means clustering technique.

Result and Discussion:

The study focuses on finding the similarities between the codons of amino acids in different countries that are affected in a similar way during COVID-19. For instance, China and the EU have a lower mortality rate and have Leucine, Methionine, Isoleucine, and Valine amino acids in common. On the other hand, countries like Pakistan and India have Leucine, Isoleucine, Valine, and Threonine in common and an average death rate. Moreover, Brazil and the US have a higher mortality rate and share similar codons such as Leucine, Glutamine, and Amber.

Concluding Remarks:

The study shows that countries affected by COVID-19 in a similar way share some common amino acids and their respective codons.

Author Biographies

Naeem A. Mahoto, Department of Software Engineering, Mehran University of Engineering & Technology Jamshoro, Pakistan.

Naeem Ahmed Mahoto received Master degree in Computer Engineering from Mehran University of Engineering and Technology, Pakistan and Ph.D in Information and System Engineering from Politecnico di Torino, Italy in 2013. He is currently working as Associate Professor/Chairman of Department of Software Engineering, Mehran UET Pakistan. His research interests are focused in the field of data science and bioinformatics. His research activities are also devoted to concept extraction, data visualization, Hybrid classification and educational data mining. He is member of IEEE Computer society and Pakistan Engineering Council (PEC).

Sania Bhatti, Department of Software Engineering, Mehran University of Engineering & Technology Jamshoro, Pakistan.

Dr. Sania Bhatti is working with the Department of Software Engineering, Mehran UET, Jamshoro, Sindh, Pakistan. She completed her PhD degree from the University of Leeds, United Kingdom in 2010 under the scholarship of faculty development program. Her research interests include modelling and simulation, communication networks and software engineering. She has published around twenty journal papers and various International conference papers.

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