SARS2020: an integrated platform for identification of novel coronavirus by a consensus sequence-function model.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 32871007.
- Also identified by DOI 10.1093/bioinformatics/btaa767 and PMC identifier 7558763.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
The 2019 novel coronavirus outbreak has significantly affected global health and society. Thus, predicting biological function from pathogen sequence is crucial and urgently needed. However, little work has been conducted to identify viruses by the enzymes that they encode, and which are key to pathogen propagation. We built a comprehensive scientific resource, SARS2020, which integrates coronavirus-related research, genomic sequences and results of anti-viral drug trials. In addition, we built a consensus sequence-catalytic function model from which we identified the novel coronavirus as encoding the same proteinase as the severe acute respiratory syndrome virus. This data-driven sequence-based strategy will enable rapid identification of agents responsible for future epidemics. SARS2020 is available at http://design.rxnfinder.org/sars2020/. Supplementary data are available at Bioinformatics online.
Medical subject headings
- COVID-19
- Severe acute respiratory syndrome-related coronavirus