Optimal entropic properties of SARS-CoV-2 RNA sequences.

ABSTRACT: The reaction of the scientific community against the COVID-19 pandemic has generated a huge (approx. 10⁶ entries) dataset of genome sequences collected worldwide and spanning a relatively short time window. These unprecedented conditions together with the certain identification of the reference viral genome sequence allow for an original statistical study of mutations in the virus genome. In this paper, we compute the Shannon entropy of every sequence in the dataset as well as the relative entropy and the mutual information between the reference sequence and the mutated ones. These functions, originally developed in information theory, measure the information content of a sequence and allows us to study the random character of mutation mechanism in terms of its entropy and infor

SUBMITTER: Formentin M 

PROVIDER: S-EPMC10827432 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature