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SARS2020: An integrated platform for identification of novel coronavirus by a consensus sequence-function model

Dachuan Zhang, Tong Zhang, Sheng Liu, Dandan Sun, Shaozhen Ding, Xingxiang Cheng, Pengli Cai, Ailin Ren, Mengying Han, Dongliang Liu, Cancan Jia, Linlin Gong (+6 others)
<span title="2020-09-01">2020</span> <i title="Oxford University Press (OUP)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wmo54ba2jnemdingjj4fl3736a" style="color: black;">Bioinformatics</a> </i> &nbsp;
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.  ...  Results We built a comprehensive scientific resource, SARS2020, that integrates coronavirus-related research, genomic sequences, and results of anti-viral drug trials.  ...  Summary We built an integrated platform to assist 2019-nCoV research, and we proposed a novel consensus sequence-function model for using genome sequence data to identify unknown species.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1093/bioinformatics/btaa767">doi:10.1093/bioinformatics/btaa767</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32871007">pmid:32871007</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vsdveahvpje4pggju6ije772yq">fatcat:vsdveahvpje4pggju6ije772yq</a> </span>
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