We apply the new GenomeBits method to uncover underlying genomic features of omicron and delta coronavirus variants. This is a statistical algorithm whose salient feature is to map the nucleotide bases into a finite alternating (±) sum series of distributed terms of binary (0,1) indicators. We show how by this method, distinctive signals can be uncovered out of the intrinsic data organization of amino acid progressions along their base positions. Results reveal a sort of 'ordered' (or constant) to 'disordered' (or peaked) transition around the coronavirus S-spike protein region. Together with our previous results for past variants of coronavirus: Alpha, Beta, Gamma, Epsilon and Eta, we conclude that the mapping into GenomeBits strands of omicron and delta variants can help to characterize mutant pathogens.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9273097PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0271039PLOS

Publication Analysis

Top Keywords

omicron delta
12
delta variants
8
variants coronavirus
8
genomebits insight
4
insight omicron
4
variants
4
coronavirus
4
coronavirus pathogen
4
pathogen apply
4
apply genomebits
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!