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Analyzing COVID-19 virus based on enhanced fragmented biological Local Aligner using improved Ions Motion

Mohamed Issa1, Mohamed Abd Elaziz2,3

  • 1Computer and Systems Department, Faculty of Engineering, Zagazig University, Zagazig 44519, Egypt.

Applied Soft Computing
|September 9, 2020
PubMed
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This summary is machine-generated.

This study enhances the Fragmented Local Aligner Technique (FLAT) using modified Ions Motion Optimization (IMO) to efficiently detect the longest common consecutive subsequence (LCCS) in SARS-CoV-2 (COVID-19) viral sequences.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Virology

Background:

  • The COVID-19 pandemic necessitates advanced tools for analyzing SARS-CoV-2.
  • Fragmented Local Aligner Technique (FLAT) identifies longest common consecutive subsequences (LCCS) in biological data.
  • Enhancing existing analytical tools is crucial for virological research.

Purpose of the Study:

  • To enhance the Fragmented Local Aligner Technique (FLAT) for improved COVID-19 analysis.
  • To develop a modified Ions Motion Optimization (IMO) algorithm for FLAT.
  • To efficiently detect the longest common consecutive subsequence (LCCS) between SARS-CoV-2 and other viral sequences.

Main Methods:

  • Modification of the Ions Motion Optimization (IMO) algorithm.
  • Integration of the enhanced IMO with the Fragmented Local Aligner Technique (FLAT).
Keywords:
COVID-19 virusIons motion optimizationLongest common consecutive substringsPairwise local alignmentSmith–Waterman alignment algorithm

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  • Testing the enhanced FLAT model on SARS-CoV-2 Orflab poly-protein and surface glycoprotein sequences.

    • Main Results:

    • The enhanced FLAT model demonstrated efficient performance in finding LCCS.
    • The proposed method achieved acceptable LCCS results in a reasonable time.
    • Experimental results showed superior LCCS detection compared to other algorithms, validated against the SW algorithm.

    Conclusions:

    • The enhanced FLAT, utilizing modified IMO, is an effective tool for SARS-CoV-2 sequence analysis.
    • This approach provides efficient and acceptable LCCS detection for virological studies.
    • The improved FLAT aids in understanding viral relationships and biological operations.