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LitCovid-PD-FMA-UBERON

{"project":"LitCovid-PD-FMA-UBERON","denotations":[{"id":"T119","span":{"begin":17,"end":21},"obj":"Body_part"},{"id":"T120","span":{"begin":72,"end":77},"obj":"Body_part"},{"id":"T121","span":{"begin":154,"end":158},"obj":"Body_part"},{"id":"T122","span":{"begin":237,"end":253},"obj":"Body_part"},{"id":"T123","span":{"begin":248,"end":253},"obj":"Body_part"},{"id":"T124","span":{"begin":263,"end":267},"obj":"Body_part"},{"id":"T125","span":{"begin":275,"end":279},"obj":"Body_part"},{"id":"T126","span":{"begin":481,"end":485},"obj":"Body_part"},{"id":"T127","span":{"begin":661,"end":665},"obj":"Body_part"},{"id":"T128","span":{"begin":790,"end":795},"obj":"Body_part"},{"id":"T129","span":{"begin":1404,"end":1408},"obj":"Body_part"}],"attributes":[{"id":"A119","pred":"fma_id","subj":"T119","obj":"http://purl.org/sig/ont/fma/fma74402"},{"id":"A120","pred":"fma_id","subj":"T120","obj":"http://purl.org/sig/ont/fma/fma68646"},{"id":"A121","pred":"fma_id","subj":"T121","obj":"http://purl.org/sig/ont/fma/fma74402"},{"id":"A122","pred":"fma_id","subj":"T122","obj":"http://purl.org/sig/ont/fma/fma66768"},{"id":"A123","pred":"fma_id","subj":"T123","obj":"http://purl.org/sig/ont/fma/fma68646"},{"id":"A124","pred":"fma_id","subj":"T124","obj":"http://purl.org/sig/ont/fma/fma7195"},{"id":"A125","pred":"fma_id","subj":"T125","obj":"http://purl.org/sig/ont/fma/fma68646"},{"id":"A126","pred":"fma_id","subj":"T126","obj":"http://purl.org/sig/ont/fma/fma74402"},{"id":"A127","pred":"fma_id","subj":"T127","obj":"http://purl.org/sig/ont/fma/fma12520"},{"id":"A128","pred":"fma_id","subj":"T128","obj":"http://purl.org/sig/ont/fma/fma68646"},{"id":"A129","pred":"fma_id","subj":"T129","obj":"http://purl.org/sig/ont/fma/fma68646"}],"text":"3.2. Analysis of Gene Alterations in NHEB Bronchial Epithelial and A549 Cells Due to SARS-CoV-2 Infection\nIn the final part of the study, we analyzed the gene expression alterations due to SARS-CoV-2-mediated infection in NHEB bronchial epithelial cells and A549 lung cancer cell lines. For this purpose, we used the Bioproject PRJNA615032 publicly available data with the Rosalind bioinformatics data analysis server.\nThe meta-analysis results were evaluated for the differential gene expression at a 1.5 fold change cut-off level. In total, 124 genes were selected according to a statistical p value threshold of \u003c0.05, and analyzed for the related signaling axis to understand the disease pathophysiology, as shown in Figure 2A,B. While 104 genes were upregulated in SARS-CoV-2-infected cells, 20 genes were downregulated.\nAll of these genes were also analysed using cluster analysis tools provided by the Rosalind bioinformatic data analysis server for different pathways. As shown in Table 4, the Wiki pathways, Bioplanet, KEGG, REACTOME, Panther, Pathway Interaction DB, and the number of virus-host response pathways, were significantly altered. These significantly altered pathways showed correspondingly similar patterns with SARS-CoV-2-mediated known clinical pathologies. These pathways were based on major differences of the target genes for inflammation responses.\nThe predicted pathways in cell lines showed similar significance with selected miRs that mainly target inflammation and virus pathogenesis (Figure 1 and Table 2). Thus, we concluded that the selected miRs, that showed high similarity with human miRs, are also the critical targets, which project the major clinical pathophysiological conditions related to pathway alterations."}

LitCovid-PD-UBERON

{"project":"LitCovid-PD-UBERON","denotations":[{"id":"T13","span":{"begin":263,"end":267},"obj":"Body_part"}],"attributes":[{"id":"A13","pred":"uberon_id","subj":"T13","obj":"http://purl.obolibrary.org/obo/UBERON_0002048"}],"text":"3.2. Analysis of Gene Alterations in NHEB Bronchial Epithelial and A549 Cells Due to SARS-CoV-2 Infection\nIn the final part of the study, we analyzed the gene expression alterations due to SARS-CoV-2-mediated infection in NHEB bronchial epithelial cells and A549 lung cancer cell lines. For this purpose, we used the Bioproject PRJNA615032 publicly available data with the Rosalind bioinformatics data analysis server.\nThe meta-analysis results were evaluated for the differential gene expression at a 1.5 fold change cut-off level. In total, 124 genes were selected according to a statistical p value threshold of \u003c0.05, and analyzed for the related signaling axis to understand the disease pathophysiology, as shown in Figure 2A,B. While 104 genes were upregulated in SARS-CoV-2-infected cells, 20 genes were downregulated.\nAll of these genes were also analysed using cluster analysis tools provided by the Rosalind bioinformatic data analysis server for different pathways. As shown in Table 4, the Wiki pathways, Bioplanet, KEGG, REACTOME, Panther, Pathway Interaction DB, and the number of virus-host response pathways, were significantly altered. These significantly altered pathways showed correspondingly similar patterns with SARS-CoV-2-mediated known clinical pathologies. These pathways were based on major differences of the target genes for inflammation responses.\nThe predicted pathways in cell lines showed similar significance with selected miRs that mainly target inflammation and virus pathogenesis (Figure 1 and Table 2). Thus, we concluded that the selected miRs, that showed high similarity with human miRs, are also the critical targets, which project the major clinical pathophysiological conditions related to pathway alterations."}

LitCovid-PD-MONDO

{"project":"LitCovid-PD-MONDO","denotations":[{"id":"T75","span":{"begin":85,"end":93},"obj":"Disease"},{"id":"T76","span":{"begin":96,"end":105},"obj":"Disease"},{"id":"T77","span":{"begin":189,"end":197},"obj":"Disease"},{"id":"T78","span":{"begin":209,"end":218},"obj":"Disease"},{"id":"T79","span":{"begin":263,"end":274},"obj":"Disease"},{"id":"T80","span":{"begin":268,"end":274},"obj":"Disease"},{"id":"T81","span":{"begin":770,"end":778},"obj":"Disease"},{"id":"T82","span":{"begin":1235,"end":1243},"obj":"Disease"},{"id":"T83","span":{"begin":1354,"end":1366},"obj":"Disease"},{"id":"T84","span":{"begin":1481,"end":1493},"obj":"Disease"}],"attributes":[{"id":"A75","pred":"mondo_id","subj":"T75","obj":"http://purl.obolibrary.org/obo/MONDO_0005091"},{"id":"A76","pred":"mondo_id","subj":"T76","obj":"http://purl.obolibrary.org/obo/MONDO_0005550"},{"id":"A77","pred":"mondo_id","subj":"T77","obj":"http://purl.obolibrary.org/obo/MONDO_0005091"},{"id":"A78","pred":"mondo_id","subj":"T78","obj":"http://purl.obolibrary.org/obo/MONDO_0005550"},{"id":"A79","pred":"mondo_id","subj":"T79","obj":"http://purl.obolibrary.org/obo/MONDO_0008903"},{"id":"A80","pred":"mondo_id","subj":"T80","obj":"http://purl.obolibrary.org/obo/MONDO_0004992"},{"id":"A81","pred":"mondo_id","subj":"T81","obj":"http://purl.obolibrary.org/obo/MONDO_0005091"},{"id":"A82","pred":"mondo_id","subj":"T82","obj":"http://purl.obolibrary.org/obo/MONDO_0005091"},{"id":"A83","pred":"mondo_id","subj":"T83","obj":"http://purl.obolibrary.org/obo/MONDO_0021166"},{"id":"A84","pred":"mondo_id","subj":"T84","obj":"http://purl.obolibrary.org/obo/MONDO_0021166"}],"text":"3.2. Analysis of Gene Alterations in NHEB Bronchial Epithelial and A549 Cells Due to SARS-CoV-2 Infection\nIn the final part of the study, we analyzed the gene expression alterations due to SARS-CoV-2-mediated infection in NHEB bronchial epithelial cells and A549 lung cancer cell lines. For this purpose, we used the Bioproject PRJNA615032 publicly available data with the Rosalind bioinformatics data analysis server.\nThe meta-analysis results were evaluated for the differential gene expression at a 1.5 fold change cut-off level. In total, 124 genes were selected according to a statistical p value threshold of \u003c0.05, and analyzed for the related signaling axis to understand the disease pathophysiology, as shown in Figure 2A,B. While 104 genes were upregulated in SARS-CoV-2-infected cells, 20 genes were downregulated.\nAll of these genes were also analysed using cluster analysis tools provided by the Rosalind bioinformatic data analysis server for different pathways. As shown in Table 4, the Wiki pathways, Bioplanet, KEGG, REACTOME, Panther, Pathway Interaction DB, and the number of virus-host response pathways, were significantly altered. These significantly altered pathways showed correspondingly similar patterns with SARS-CoV-2-mediated known clinical pathologies. These pathways were based on major differences of the target genes for inflammation responses.\nThe predicted pathways in cell lines showed similar significance with selected miRs that mainly target inflammation and virus pathogenesis (Figure 1 and Table 2). Thus, we concluded that the selected miRs, that showed high similarity with human miRs, are also the critical targets, which project the major clinical pathophysiological conditions related to pathway alterations."}

LitCovid-PD-CLO

LitCovid-PD-CHEBI

{"project":"LitCovid-PD-CHEBI","denotations":[{"id":"T56","span":{"begin":1053,"end":1060},"obj":"Chemical"}],"attributes":[{"id":"A56","pred":"chebi_id","subj":"T56","obj":"http://purl.obolibrary.org/obo/CHEBI_34922"}],"text":"3.2. Analysis of Gene Alterations in NHEB Bronchial Epithelial and A549 Cells Due to SARS-CoV-2 Infection\nIn the final part of the study, we analyzed the gene expression alterations due to SARS-CoV-2-mediated infection in NHEB bronchial epithelial cells and A549 lung cancer cell lines. For this purpose, we used the Bioproject PRJNA615032 publicly available data with the Rosalind bioinformatics data analysis server.\nThe meta-analysis results were evaluated for the differential gene expression at a 1.5 fold change cut-off level. In total, 124 genes were selected according to a statistical p value threshold of \u003c0.05, and analyzed for the related signaling axis to understand the disease pathophysiology, as shown in Figure 2A,B. While 104 genes were upregulated in SARS-CoV-2-infected cells, 20 genes were downregulated.\nAll of these genes were also analysed using cluster analysis tools provided by the Rosalind bioinformatic data analysis server for different pathways. As shown in Table 4, the Wiki pathways, Bioplanet, KEGG, REACTOME, Panther, Pathway Interaction DB, and the number of virus-host response pathways, were significantly altered. These significantly altered pathways showed correspondingly similar patterns with SARS-CoV-2-mediated known clinical pathologies. These pathways were based on major differences of the target genes for inflammation responses.\nThe predicted pathways in cell lines showed similar significance with selected miRs that mainly target inflammation and virus pathogenesis (Figure 1 and Table 2). Thus, we concluded that the selected miRs, that showed high similarity with human miRs, are also the critical targets, which project the major clinical pathophysiological conditions related to pathway alterations."}

LitCovid-PD-HP

{"project":"LitCovid-PD-HP","denotations":[{"id":"T20","span":{"begin":263,"end":274},"obj":"Phenotype"}],"attributes":[{"id":"A20","pred":"hp_id","subj":"T20","obj":"http://purl.obolibrary.org/obo/HP_0100526"}],"text":"3.2. Analysis of Gene Alterations in NHEB Bronchial Epithelial and A549 Cells Due to SARS-CoV-2 Infection\nIn the final part of the study, we analyzed the gene expression alterations due to SARS-CoV-2-mediated infection in NHEB bronchial epithelial cells and A549 lung cancer cell lines. For this purpose, we used the Bioproject PRJNA615032 publicly available data with the Rosalind bioinformatics data analysis server.\nThe meta-analysis results were evaluated for the differential gene expression at a 1.5 fold change cut-off level. In total, 124 genes were selected according to a statistical p value threshold of \u003c0.05, and analyzed for the related signaling axis to understand the disease pathophysiology, as shown in Figure 2A,B. While 104 genes were upregulated in SARS-CoV-2-infected cells, 20 genes were downregulated.\nAll of these genes were also analysed using cluster analysis tools provided by the Rosalind bioinformatic data analysis server for different pathways. As shown in Table 4, the Wiki pathways, Bioplanet, KEGG, REACTOME, Panther, Pathway Interaction DB, and the number of virus-host response pathways, were significantly altered. These significantly altered pathways showed correspondingly similar patterns with SARS-CoV-2-mediated known clinical pathologies. These pathways were based on major differences of the target genes for inflammation responses.\nThe predicted pathways in cell lines showed similar significance with selected miRs that mainly target inflammation and virus pathogenesis (Figure 1 and Table 2). Thus, we concluded that the selected miRs, that showed high similarity with human miRs, are also the critical targets, which project the major clinical pathophysiological conditions related to pathway alterations."}

LitCovid-PD-GO-BP

{"project":"LitCovid-PD-GO-BP","denotations":[{"id":"T59","span":{"begin":154,"end":169},"obj":"http://purl.obolibrary.org/obo/GO_0010467"},{"id":"T60","span":{"begin":481,"end":496},"obj":"http://purl.obolibrary.org/obo/GO_0010467"},{"id":"T61","span":{"begin":651,"end":660},"obj":"http://purl.obolibrary.org/obo/GO_0023052"},{"id":"T62","span":{"begin":1354,"end":1366},"obj":"http://purl.obolibrary.org/obo/GO_0006954"},{"id":"T63","span":{"begin":1481,"end":1493},"obj":"http://purl.obolibrary.org/obo/GO_0006954"},{"id":"T64","span":{"begin":1504,"end":1516},"obj":"http://purl.obolibrary.org/obo/GO_0009405"}],"text":"3.2. Analysis of Gene Alterations in NHEB Bronchial Epithelial and A549 Cells Due to SARS-CoV-2 Infection\nIn the final part of the study, we analyzed the gene expression alterations due to SARS-CoV-2-mediated infection in NHEB bronchial epithelial cells and A549 lung cancer cell lines. For this purpose, we used the Bioproject PRJNA615032 publicly available data with the Rosalind bioinformatics data analysis server.\nThe meta-analysis results were evaluated for the differential gene expression at a 1.5 fold change cut-off level. In total, 124 genes were selected according to a statistical p value threshold of \u003c0.05, and analyzed for the related signaling axis to understand the disease pathophysiology, as shown in Figure 2A,B. While 104 genes were upregulated in SARS-CoV-2-infected cells, 20 genes were downregulated.\nAll of these genes were also analysed using cluster analysis tools provided by the Rosalind bioinformatic data analysis server for different pathways. As shown in Table 4, the Wiki pathways, Bioplanet, KEGG, REACTOME, Panther, Pathway Interaction DB, and the number of virus-host response pathways, were significantly altered. These significantly altered pathways showed correspondingly similar patterns with SARS-CoV-2-mediated known clinical pathologies. These pathways were based on major differences of the target genes for inflammation responses.\nThe predicted pathways in cell lines showed similar significance with selected miRs that mainly target inflammation and virus pathogenesis (Figure 1 and Table 2). Thus, we concluded that the selected miRs, that showed high similarity with human miRs, are also the critical targets, which project the major clinical pathophysiological conditions related to pathway alterations."}

LitCovid-sentences

{"project":"LitCovid-sentences","denotations":[{"id":"T140","span":{"begin":0,"end":4},"obj":"Sentence"},{"id":"T141","span":{"begin":5,"end":105},"obj":"Sentence"},{"id":"T142","span":{"begin":106,"end":286},"obj":"Sentence"},{"id":"T143","span":{"begin":287,"end":418},"obj":"Sentence"},{"id":"T144","span":{"begin":419,"end":532},"obj":"Sentence"},{"id":"T145","span":{"begin":533,"end":733},"obj":"Sentence"},{"id":"T146","span":{"begin":734,"end":825},"obj":"Sentence"},{"id":"T147","span":{"begin":826,"end":976},"obj":"Sentence"},{"id":"T148","span":{"begin":977,"end":1152},"obj":"Sentence"},{"id":"T149","span":{"begin":1153,"end":1282},"obj":"Sentence"},{"id":"T150","span":{"begin":1283,"end":1377},"obj":"Sentence"},{"id":"T151","span":{"begin":1378,"end":1540},"obj":"Sentence"},{"id":"T152","span":{"begin":1541,"end":1754},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"3.2. Analysis of Gene Alterations in NHEB Bronchial Epithelial and A549 Cells Due to SARS-CoV-2 Infection\nIn the final part of the study, we analyzed the gene expression alterations due to SARS-CoV-2-mediated infection in NHEB bronchial epithelial cells and A549 lung cancer cell lines. For this purpose, we used the Bioproject PRJNA615032 publicly available data with the Rosalind bioinformatics data analysis server.\nThe meta-analysis results were evaluated for the differential gene expression at a 1.5 fold change cut-off level. In total, 124 genes were selected according to a statistical p value threshold of \u003c0.05, and analyzed for the related signaling axis to understand the disease pathophysiology, as shown in Figure 2A,B. While 104 genes were upregulated in SARS-CoV-2-infected cells, 20 genes were downregulated.\nAll of these genes were also analysed using cluster analysis tools provided by the Rosalind bioinformatic data analysis server for different pathways. As shown in Table 4, the Wiki pathways, Bioplanet, KEGG, REACTOME, Panther, Pathway Interaction DB, and the number of virus-host response pathways, were significantly altered. These significantly altered pathways showed correspondingly similar patterns with SARS-CoV-2-mediated known clinical pathologies. These pathways were based on major differences of the target genes for inflammation responses.\nThe predicted pathways in cell lines showed similar significance with selected miRs that mainly target inflammation and virus pathogenesis (Figure 1 and Table 2). Thus, we concluded that the selected miRs, that showed high similarity with human miRs, are also the critical targets, which project the major clinical pathophysiological conditions related to pathway alterations."}

LitCovid-PubTator

{"project":"LitCovid-PubTator","denotations":[{"id":"364","span":{"begin":85,"end":105},"obj":"Disease"},{"id":"365","span":{"begin":67,"end":71},"obj":"CellLine"},{"id":"370","span":{"begin":189,"end":199},"obj":"Species"},{"id":"371","span":{"begin":209,"end":218},"obj":"Disease"},{"id":"372","span":{"begin":263,"end":274},"obj":"Disease"},{"id":"373","span":{"begin":258,"end":262},"obj":"CellLine"},{"id":"375","span":{"begin":770,"end":789},"obj":"Disease"},{"id":"378","span":{"begin":1235,"end":1245},"obj":"Species"},{"id":"379","span":{"begin":1354,"end":1366},"obj":"Disease"},{"id":"382","span":{"begin":1617,"end":1622},"obj":"Species"},{"id":"383","span":{"begin":1481,"end":1493},"obj":"Disease"}],"attributes":[{"id":"A364","pred":"tao:has_database_id","subj":"364","obj":"MESH:C000657245"},{"id":"A365","pred":"tao:has_database_id","subj":"365","obj":"CVCL:0023"},{"id":"A370","pred":"tao:has_database_id","subj":"370","obj":"Tax:2697049"},{"id":"A371","pred":"tao:has_database_id","subj":"371","obj":"MESH:D007239"},{"id":"A372","pred":"tao:has_database_id","subj":"372","obj":"MESH:D008175"},{"id":"A373","pred":"tao:has_database_id","subj":"373","obj":"CVCL:0023"},{"id":"A375","pred":"tao:has_database_id","subj":"375","obj":"MESH:C000657245"},{"id":"A378","pred":"tao:has_database_id","subj":"378","obj":"Tax:2697049"},{"id":"A379","pred":"tao:has_database_id","subj":"379","obj":"MESH:D007249"},{"id":"A382","pred":"tao:has_database_id","subj":"382","obj":"Tax:9606"},{"id":"A383","pred":"tao:has_database_id","subj":"383","obj":"MESH:D007249"}],"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":"3.2. Analysis of Gene Alterations in NHEB Bronchial Epithelial and A549 Cells Due to SARS-CoV-2 Infection\nIn the final part of the study, we analyzed the gene expression alterations due to SARS-CoV-2-mediated infection in NHEB bronchial epithelial cells and A549 lung cancer cell lines. For this purpose, we used the Bioproject PRJNA615032 publicly available data with the Rosalind bioinformatics data analysis server.\nThe meta-analysis results were evaluated for the differential gene expression at a 1.5 fold change cut-off level. In total, 124 genes were selected according to a statistical p value threshold of \u003c0.05, and analyzed for the related signaling axis to understand the disease pathophysiology, as shown in Figure 2A,B. While 104 genes were upregulated in SARS-CoV-2-infected cells, 20 genes were downregulated.\nAll of these genes were also analysed using cluster analysis tools provided by the Rosalind bioinformatic data analysis server for different pathways. As shown in Table 4, the Wiki pathways, Bioplanet, KEGG, REACTOME, Panther, Pathway Interaction DB, and the number of virus-host response pathways, were significantly altered. These significantly altered pathways showed correspondingly similar patterns with SARS-CoV-2-mediated known clinical pathologies. These pathways were based on major differences of the target genes for inflammation responses.\nThe predicted pathways in cell lines showed similar significance with selected miRs that mainly target inflammation and virus pathogenesis (Figure 1 and Table 2). Thus, we concluded that the selected miRs, that showed high similarity with human miRs, are also the critical targets, which project the major clinical pathophysiological conditions related to pathway alterations."}

PMC:7354481 / 20816-22570 JSONTXT

Annnotations TAB JSON ListView MergeView

PMC:7354481 / 20816-22570 JSON TXT