PMC:7253482 / 33392-34338 JSONTXT

{"project":"LitCovid-PubTator","denotations":[{"id":"1010","span":{"begin":94,"end":102},"obj":"Species"},{"id":"1011","span":{"begin":645,"end":647},"obj":"Chemical"},{"id":"1012","span":{"begin":648,"end":650},"obj":"Chemical"},{"id":"1013","span":{"begin":84,"end":88},"obj":"Disease"}],"attributes":[{"id":"A1010","pred":"tao:has_database_id","subj":"1010","obj":"Tax:1335626"},{"id":"A1011","pred":"tao:has_database_id","subj":"1011","obj":"MESH:C022306"},{"id":"A1012","pred":"tao:has_database_id","subj":"1012","obj":"MESH:D003903"},{"id":"A1013","pred":"tao:has_database_id","subj":"1013","obj":"MESH:D045169"}],"namespaces":[{"prefix":"Tax","uri":"https://www.ncbi.nlm.nih.gov/taxonomy/"},{"prefix":"MESH","uri":"https://id.nlm.nih.gov/mesh/"},{"prefix":"Gene","uri":"https://www.ncbi.nlm.nih.gov/gene/"},{"prefix":"CVCL","uri":"https://web.expasy.org/cellosaurus/CVCL_"}],"text":"For the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-PD-FMA-UBERON","denotations":[{"id":"T172","span":{"begin":760,"end":770},"obj":"Body_part"},{"id":"T173","span":{"begin":828,"end":838},"obj":"Body_part"},{"id":"T174","span":{"begin":878,"end":888},"obj":"Body_part"}],"attributes":[{"id":"A172","pred":"fma_id","subj":"T172","obj":"http://purl.org/sig/ont/fma/fma82739"},{"id":"A173","pred":"fma_id","subj":"T173","obj":"http://purl.org/sig/ont/fma/fma82739"},{"id":"A174","pred":"fma_id","subj":"T174","obj":"http://purl.org/sig/ont/fma/fma82739"}],"text":"For the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-PD-MONDO","denotations":[{"id":"T102","span":{"begin":84,"end":88},"obj":"Disease"}],"attributes":[{"id":"A102","pred":"mondo_id","subj":"T102","obj":"http://purl.obolibrary.org/obo/MONDO_0005091"}],"text":"For the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T240","span":{"begin":149,"end":156},"obj":"http://purl.obolibrary.org/obo/NCBITaxon_10239"},{"id":"T241","span":{"begin":267,"end":268},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T242","span":{"begin":551,"end":560},"obj":"http://purl.obolibrary.org/obo/UBERON_0001353"}],"text":"For the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-PD-CHEBI","denotations":[{"id":"T357","span":{"begin":8,"end":10},"obj":"Chemical"},{"id":"T358","span":{"begin":645,"end":647},"obj":"Chemical"},{"id":"T359","span":{"begin":760,"end":765},"obj":"Chemical"},{"id":"T360","span":{"begin":766,"end":770},"obj":"Chemical"},{"id":"T361","span":{"begin":828,"end":833},"obj":"Chemical"},{"id":"T362","span":{"begin":834,"end":838},"obj":"Chemical"},{"id":"T363","span":{"begin":878,"end":883},"obj":"Chemical"},{"id":"T364","span":{"begin":884,"end":888},"obj":"Chemical"}],"attributes":[{"id":"A357","pred":"chebi_id","subj":"T357","obj":"http://purl.obolibrary.org/obo/CHEBI_33793"},{"id":"A358","pred":"chebi_id","subj":"T358","obj":"http://purl.obolibrary.org/obo/CHEBI_33793"},{"id":"A359","pred":"chebi_id","subj":"T359","obj":"http://purl.obolibrary.org/obo/CHEBI_46882"},{"id":"A360","pred":"chebi_id","subj":"T360","obj":"http://purl.obolibrary.org/obo/CHEBI_37527"},{"id":"A361","pred":"chebi_id","subj":"T361","obj":"http://purl.obolibrary.org/obo/CHEBI_46882"},{"id":"A362","pred":"chebi_id","subj":"T362","obj":"http://purl.obolibrary.org/obo/CHEBI_37527"},{"id":"A363","pred":"chebi_id","subj":"T363","obj":"http://purl.obolibrary.org/obo/CHEBI_46882"},{"id":"A364","pred":"chebi_id","subj":"T364","obj":"http://purl.obolibrary.org/obo/CHEBI_37527"}],"text":"For the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-sample-PD-IDO","denotations":[{"id":"T92","span":{"begin":149,"end":156},"obj":"http://purl.obolibrary.org/obo/NCBITaxon_10239"},{"id":"T93","span":{"begin":755,"end":759},"obj":"http://purl.obolibrary.org/obo/BFO_0000029"}],"text":"For the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-sample-PD-FMA","denotations":[{"id":"T170","span":{"begin":760,"end":770},"obj":"Body_part"},{"id":"T171","span":{"begin":828,"end":838},"obj":"Body_part"},{"id":"T172","span":{"begin":878,"end":888},"obj":"Body_part"}],"attributes":[{"id":"A172","pred":"fma_id","subj":"T172","obj":"http://purl.org/sig/ont/fma/fma82739"},{"id":"A170","pred":"fma_id","subj":"T170","obj":"http://purl.org/sig/ont/fma/fma82739"},{"id":"A171","pred":"fma_id","subj":"T171","obj":"http://purl.org/sig/ont/fma/fma82739"}],"text":"For the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-sample-CHEBI","denotations":[{"id":"T251","span":{"begin":760,"end":765},"obj":"Chemical"},{"id":"T252","span":{"begin":828,"end":833},"obj":"Chemical"},{"id":"T253","span":{"begin":878,"end":883},"obj":"Chemical"}],"attributes":[{"id":"A252","pred":"chebi_id","subj":"T252","obj":"http://purl.obolibrary.org/obo/CHEBI_46882"},{"id":"A253","pred":"chebi_id","subj":"T253","obj":"http://purl.obolibrary.org/obo/CHEBI_46882"},{"id":"A251","pred":"chebi_id","subj":"T251","obj":"http://purl.obolibrary.org/obo/CHEBI_46882"}],"text":"For the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-sample-PD-NCBITaxon","denotations":[{"id":"T211","span":{"begin":84,"end":88},"obj":"Species"},{"id":"T212","span":{"begin":94,"end":102},"obj":"Species"},{"id":"T213","span":{"begin":149,"end":156},"obj":"Species"},{"id":"T214","span":{"begin":269,"end":274},"obj":"Species"}],"attributes":[{"id":"A211","pred":"ncbi_taxonomy_id","subj":"T211","obj":"NCBItxid:694009"},{"id":"A212","pred":"ncbi_taxonomy_id","subj":"T212","obj":"NCBItxid:1335626"},{"id":"A213","pred":"ncbi_taxonomy_id","subj":"T213","obj":"NCBItxid:10239"},{"id":"A214","pred":"ncbi_taxonomy_id","subj":"T214","obj":"NCBItxid:79338"}],"namespaces":[{"prefix":"NCBItxid","uri":"http://purl.bioontology.org/ontology/NCBITAXON/"}],"text":"For the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-sample-sentences","denotations":[{"id":"T201","span":{"begin":0,"end":139},"obj":"Sentence"},{"id":"T202","span":{"begin":140,"end":307},"obj":"Sentence"},{"id":"T203","span":{"begin":308,"end":438},"obj":"Sentence"},{"id":"T204","span":{"begin":439,"end":732},"obj":"Sentence"},{"id":"T205","span":{"begin":733,"end":946},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"For the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-sample-PD-MONDO","denotations":[{"id":"T97","span":{"begin":84,"end":88},"obj":"Disease"}],"attributes":[{"id":"A97","pred":"mondo_id","subj":"T97","obj":"http://purl.obolibrary.org/obo/MONDO_0005091"}],"text":"For the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-sample-Pubtator","denotations":[{"id":"1013","span":{"begin":84,"end":88},"obj":"Disease"},{"id":"1010","span":{"begin":94,"end":102},"obj":"Species"},{"id":"1011","span":{"begin":645,"end":647},"obj":"Chemical"},{"id":"1012","span":{"begin":648,"end":650},"obj":"Chemical"}],"attributes":[{"id":"A1010","pred":"pubann:denotes","subj":"1010","obj":"Tax:1335626"},{"id":"A1013","pred":"pubann:denotes","subj":"1013","obj":"MESH:D045169"},{"id":"A1011","pred":"pubann:denotes","subj":"1011","obj":"MESH:C022306"},{"id":"A1012","pred":"pubann:denotes","subj":"1012","obj":"MESH:D003903"}],"text":"For the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-sentences","denotations":[{"id":"T201","span":{"begin":0,"end":139},"obj":"Sentence"},{"id":"T202","span":{"begin":140,"end":307},"obj":"Sentence"},{"id":"T203","span":{"begin":308,"end":438},"obj":"Sentence"},{"id":"T204","span":{"begin":439,"end":732},"obj":"Sentence"},{"id":"T205","span":{"begin":733,"end":946},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"For the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}