PLoS ONEBioinformaticsPeer-reviewed journal article
GenomeBits insight into omicron and delta variants of coronavirus pathogen
Abstract
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.
- organism: virus
- assay: whole-genome sequencing
- research focus: variant effect prediction
- approach: statistical model
- Citations
- 3
- FWCI
- 0.24
- Field percentile
- 41th percentile
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