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Uncovering Signals from the Coronavirus Genome.
Canessa, Enrique.
  • Canessa E; The Abdus Salam International Centre for Theoretical Physics (ICTP), Science Dissemination Unit (SDU), 34151 Trieste, Italy.
Genes (Basel) ; 12(7)2021 06 25.
Article in English | MEDLINE | ID: covidwho-1288842
ABSTRACT
A signal analysis of the complete genome sequenced for coronavirus variants of concern-B.1.1.7 (Alpha), B.1.135 (Beta) and P1 (Gamma)-and coronavirus variants of interest-B.1.429-B.1.427 (Epsilon) and B.1.525 (Eta)-is presented using open GISAID data. We deal with a certain new type of finite alternating sum series having independently distributed terms associated with binary (0,1) indicators for the nucleotide bases. Our method provides additional information to conventional similarity comparisons via alignment methods and Fourier Power Spectrum approaches. It leads to uncover distinctive patterns regarding the intrinsic data organization of complete genomics sequences according to its progression along the nucleotide bases position. The present new method could be useful for the bioinformatics surveillance and dynamics of coronavirus genome variants.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Viral Proteins / Genome, Viral / Computational Biology / SARS-CoV-2 Topics: Variants Limits: Humans Language: English Year: 2021 Document Type: Article Affiliation country: Genes12070973

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Viral Proteins / Genome, Viral / Computational Biology / SARS-CoV-2 Topics: Variants Limits: Humans Language: English Year: 2021 Document Type: Article Affiliation country: Genes12070973