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LitCovid-PD-FMA-UBERON

Id Subject Object Predicate Lexical cue fma_id
T1 810-818 Body_part denotes proteins http://purl.org/sig/ont/fma/fma67257
T2 1234-1239 Body_part denotes cells http://purl.org/sig/ont/fma/fma68646

LitCovid-PD-UBERON

Id Subject Object Predicate Lexical cue uberon_id
T1 875-881 Body_part denotes corpus http://purl.obolibrary.org/obo/UBERON_3000645

LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T1 49-57 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T2 172-196 Disease denotes coronavirus disease 2019 http://purl.obolibrary.org/obo/MONDO_0100096
T3 198-206 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T4 238-271 Disease denotes severe acute respiratory syndrome http://purl.obolibrary.org/obo/MONDO_0005091
T5 285-293 Disease denotes SARS-CoV http://purl.obolibrary.org/obo/MONDO_0005091
T6 401-409 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T7 516-524 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T8 636-644 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T9 1143-1151 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T10 1208-1216 Disease denotes SARS-CoV http://purl.obolibrary.org/obo/MONDO_0005091
T11 1514-1522 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T1 166-171 http://purl.obolibrary.org/obo/NCBITaxon_9606 denotes human
T2 354-355 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T3 435-436 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T4 686-687 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T5 819-824 http://purl.obolibrary.org/obo/OGG_0000000002 denotes genes
T6 856-857 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T7 960-961 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T8 1016-1018 http://purl.obolibrary.org/obo/CLO_0053794 denotes 41
T9 1228-1239 http://purl.obolibrary.org/obo/CLO_0053065 denotes human cells
T10 1353-1354 http://purl.obolibrary.org/obo/CLO_0001020 denotes a

LitCovid-PD-CHEBI

Id Subject Object Predicate Lexical cue chebi_id
T1 626-631 Chemical denotes drugs http://purl.obolibrary.org/obo/CHEBI_23888
T2 793-798 Chemical denotes drugs http://purl.obolibrary.org/obo/CHEBI_23888
T3 810-818 Chemical denotes proteins http://purl.obolibrary.org/obo/CHEBI_36080
T4 1032-1037 Chemical denotes drugs http://purl.obolibrary.org/obo/CHEBI_23888
T5 1049-1062 Chemical denotes dexamethasone http://purl.obolibrary.org/obo/CHEBI_41879
T6 1095-1105 Chemical denotes toremifene http://purl.obolibrary.org/obo/CHEBI_9635
T7 1330-1335 Chemical denotes drugs http://purl.obolibrary.org/obo/CHEBI_23888
T8 1413-1418 Chemical denotes drugs http://purl.obolibrary.org/obo/CHEBI_23888

LitCovid-PD-GO-BP

Id Subject Object Predicate Lexical cue
T1 69-77 http://purl.obolibrary.org/obo/GO_0007612 denotes Learning
T2 580-588 http://purl.obolibrary.org/obo/GO_0007612 denotes learning
T3 982-990 http://purl.obolibrary.org/obo/GO_0007612 denotes learning
T4 1369-1377 http://purl.obolibrary.org/obo/GO_0007612 denotes learning

LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
1 49-57 Disease denotes COVID-19 MESH:C000657245
19 150-156 Disease denotes deaths MESH:D003643
20 172-196 Disease denotes coronavirus disease 2019 MESH:C000657245
21 198-206 Disease denotes COVID-19 MESH:C000657245
22 238-283 Species denotes severe acute respiratory syndrome coronavirus Tax:694009
23 285-295 Species denotes SARS-CoV-2 Tax:2697049
24 401-409 Disease denotes COVID-19 MESH:C000657245
25 516-524 Disease denotes COVID-19 MESH:C000657245
26 636-644 Disease denotes COVID-19 MESH:C000657245
27 653-656 Species denotes CoV Tax:11118
28 1049-1062 Chemical denotes dexamethasone MESH:D003907
29 1064-1076 Chemical denotes indomethacin MESH:D007213
30 1078-1089 Chemical denotes niclosamide MESH:D009534
31 1095-1105 Chemical denotes toremifene MESH:D017312
32 1143-1151 Disease denotes COVID-19 MESH:C000657245
33 1208-1227 Disease denotes SARS-CoV-2-infected MESH:C000657245
34 1228-1233 Species denotes human Tax:9606
35 1514-1522 Disease denotes COVID-19 MESH:C000657245

LitCovid_AGAC_only

Id Subject Object Predicate Lexical cue
p53299s29 216-220 Reg denotes , ca

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T1 0-78 Sentence denotes Repurpose Open Data to Discover Therapeutics for COVID-19 Using Deep Learning.
T2 79-325 Sentence denotes There have been more than 2.2 million confirmed cases and over 120 000 deaths from the human coronavirus disease 2019 (COVID-19) pandemic, caused by the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), in the United States alone.
T3 326-410 Sentence denotes However, there is currently a lack of proven effective medications against COVID-19.
T4 411-525 Sentence denotes Drug repurposing offers a promising route for the development of prevention and treatment strategies for COVID-19.
T5 526-662 Sentence denotes This study reports an integrative, network-based deep-learning methodology to identify repurposable drugs for COVID-19 (termed CoV-KGE).
T6 663-916 Sentence denotes Specifically, we built a comprehensive knowledge graph that includes 15 million edges across 39 types of relationships connecting drugs, diseases, proteins/genes, pathways, and expression from a large scientific corpus of 24 million PubMed publications.
T7 917-1278 Sentence denotes Using Amazon's AWS computing resources and a network-based, deep-learning framework, we identified 41 repurposable drugs (including dexamethasone, indomethacin, niclosamide, and toremifene) whose therapeutic associations with COVID-19 were validated by transcriptomic and proteomics data in SARS-CoV-2-infected human cells and data from ongoing clinical trials.
T8 1279-1523 Sentence denotes Whereas this study by no means recommends specific drugs, it demonstrates a powerful deep-learning methodology to prioritize existing drugs for further investigation, which holds the potential to accelerate therapeutic development for COVID-19.

sentences

Id Subject Object Predicate Lexical cue
T1 0-78 Sentence denotes Repurpose Open Data to Discover Therapeutics for COVID-19 Using Deep Learning.
T2 79-325 Sentence denotes There have been more than 2.2 million confirmed cases and over 120 000 deaths from the human coronavirus disease 2019 (COVID-19) pandemic, caused by the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), in the United States alone.
T3 326-410 Sentence denotes However, there is currently a lack of proven effective medications against COVID-19.
T4 411-525 Sentence denotes Drug repurposing offers a promising route for the development of prevention and treatment strategies for COVID-19.
T5 526-662 Sentence denotes This study reports an integrative, network-based deep-learning methodology to identify repurposable drugs for COVID-19 (termed CoV-KGE).
T6 663-916 Sentence denotes Specifically, we built a comprehensive knowledge graph that includes 15 million edges across 39 types of relationships connecting drugs, diseases, proteins/genes, pathways, and expression from a large scientific corpus of 24 million PubMed publications.
T7 917-1278 Sentence denotes Using Amazon's AWS computing resources and a network-based, deep-learning framework, we identified 41 repurposable drugs (including dexamethasone, indomethacin, niclosamide, and toremifene) whose therapeutic associations with COVID-19 were validated by transcriptomic and proteomics data in SARS-CoV-2-infected human cells and data from ongoing clinical trials.
T8 1279-1523 Sentence denotes Whereas this study by no means recommends specific drugs, it demonstrates a powerful deep-learning methodology to prioritize existing drugs for further investigation, which holds the potential to accelerate therapeutic development for COVID-19.
T1 0-78 Sentence denotes Repurpose Open Data to Discover Therapeutics for COVID-19 Using Deep Learning.
T2 79-325 Sentence denotes There have been more than 2.2 million confirmed cases and over 120 000 deaths from the human coronavirus disease 2019 (COVID-19) pandemic, caused by the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), in the United States alone.
T3 326-410 Sentence denotes However, there is currently a lack of proven effective medications against COVID-19.
T4 411-525 Sentence denotes Drug repurposing offers a promising route for the development of prevention and treatment strategies for COVID-19.
T5 526-662 Sentence denotes This study reports an integrative, network-based deep-learning methodology to identify repurposable drugs for COVID-19 (termed CoV-KGE).
T6 663-916 Sentence denotes Specifically, we built a comprehensive knowledge graph that includes 15 million edges across 39 types of relationships connecting drugs, diseases, proteins/genes, pathways, and expression from a large scientific corpus of 24 million PubMed publications.
T7 917-1278 Sentence denotes Using Amazon's AWS computing resources and a network-based, deep-learning framework, we identified 41 repurposable drugs (including dexamethasone, indomethacin, niclosamide, and toremifene) whose therapeutic associations with COVID-19 were validated by transcriptomic and proteomics data in SARS-CoV-2-infected human cells and data from ongoing clinical trials.
T8 1279-1523 Sentence denotes Whereas this study by no means recommends specific drugs, it demonstrates a powerful deep-learning methodology to prioritize existing drugs for further investigation, which holds the potential to accelerate therapeutic development for COVID-19.

mondo_disease

Id Subject Object Predicate Lexical cue mondo_id
T1 49-57 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T2 172-196 Disease denotes coronavirus disease 2019 http://purl.obolibrary.org/obo/MONDO_0100096
T3 198-206 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T4 238-271 Disease denotes severe acute respiratory syndrome http://purl.obolibrary.org/obo/MONDO_0005091
T5 285-295 Disease denotes SARS-CoV-2 http://purl.obolibrary.org/obo/MONDO_0100096
T6 401-409 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T7 516-524 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T8 636-644 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T9 1143-1151 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T10 1208-1218 Disease denotes SARS-CoV-2 http://purl.obolibrary.org/obo/MONDO_0100096
T11 1514-1522 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096

NCBITAXON

Id Subject Object Predicate Lexical cue db_id
T1 166-171 OrganismTaxon denotes human 9606
T2 172-196 OrganismTaxon denotes coronavirus disease 2019 2697049
T3 238-271 OrganismTaxon denotes severe acute respiratory syndrome 694009
T4 285-293 OrganismTaxon denotes SARS-CoV 694009
T5 1208-1216 OrganismTaxon denotes SARS-CoV 694009
T6 1228-1233 OrganismTaxon denotes human 9606

Anatomy-UBERON

Id Subject Object Predicate Lexical cue uberon_id
T1 875-881 Body_part denotes corpus http://purl.obolibrary.org/obo/UBERON_0004360|http://purl.obolibrary.org/obo/UBERON_3000645