Could a mathematical application of information theory identify and predict SARS-CoV-2 mutations?

Press/Media: Research cited

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An interesting new study by Melvin Vopson at the University of Portsmouth, UK, describes the use of a mathematical method to sequence genomes based on information theory. The method offers an alternative to clinical techniques, allowing mutations to be detected and possibly even predicted. In this way, it opens new research opportunities in bioinformatics and genetics.

Period31 May 2021

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  • TitleCould a mathematical application of information theory identify and predict SARS-CoV-2 mutations?
    Degree of recognitionInternational
    Media name/outletnews-medical.net
    Media typeWeb
    Country/TerritoryUnited States
    Date31/05/21
    DescriptionThe new paper uses information theory to devise a novel method whereby mutations can be both traced and predicted in genomic sequences. This is far from being the first attempt to do this, for DNA sequences have been analyzed through methods built on information theory from the ‘70s onwards.

    The approach used in this study centers around information entropy (IE) spectra, which are created from genomic sequences, and the examination of their mutation dynamics. Importantly, this approach is relevant for any sequence of any genome of any size.

    The researchers used a program called GENIES (GENetic Entropy Information Spectrum), custom-built for this project and now available for free to other scientists
    Producer/AuthorDr. Liji Thomas
    URLhttps://www.news-medical.net/news/20210531/Could-a-mathematical-application-of-information-theory-identify-and-predict-SARS-CoV-2-mutations.aspx
    PersonsMelvin Vopson
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