Potentially adaptive SARS-CoV-2 mutations discovered with novel spatiotemporal and explainable AI models.

ABSTRACT:

Background

A mechanistic understanding of the spread of SARS-CoV-2 and diligent tracking of ongoing mutagenesis are of key importance to plan robust strategies for confining its transmission. Large numbers of available sequences and their dates of transmission provide an unprecedented opportunity to analyze evolutionary adaptation in novel ways. Addition of high-resolution structural information can reveal the functional basis of these processes at the molecular level. Integrated systems biology-directed analyses of these data layers afford valuable insights to build a global understanding of the COVID-19 pandemic.

Results

Here we identify globally distributed haplotypes from 15,789 SARS-CoV-2 genomes and model their success based on their duration, dispersal, and frequency

SUBMITTER: Garvin MR 

PROVIDER: S-EPMC7756312 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature