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PMC:7371427 / 7793-8699 JSONTXT

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LitCovid-PD-FMA-UBERON

Id Subject Object Predicate Lexical cue fma_id
T43 191-195 Body_part denotes gene http://purl.org/sig/ont/fma/fma74402
T44 200-207 Body_part denotes protein http://purl.org/sig/ont/fma/fma67257
T45 306-310 Body_part denotes Cell http://purl.org/sig/ont/fma/fma68646
T46 311-314 Body_part denotes RNA http://purl.org/sig/ont/fma/fma67095
T47 557-562 Body_part denotes cells http://purl.org/sig/ont/fma/fma68646
T48 592-598 Body_part denotes tissue http://purl.org/sig/ont/fma/fma9637
T49 728-735 Body_part denotes tissues http://purl.org/sig/ont/fma/fma9637
T50 740-744 Body_part denotes cell http://purl.org/sig/ont/fma/fma68646

LitCovid-PD-UBERON

Id Subject Object Predicate Lexical cue uberon_id
T16 592-598 Body_part denotes tissue http://purl.obolibrary.org/obo/UBERON_0000479

LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
37 876-884 Disease denotes COVID-19 MESH:C000657245

LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T33 876-884 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T73 191-195 http://purl.obolibrary.org/obo/OGG_0000000002 denotes gene
T74 297-298 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T75 306-310 http://purl.obolibrary.org/obo/GO_0005623 denotes Cell
T76 557-562 http://purl.obolibrary.org/obo/GO_0005623 denotes cells
T77 576-581 http://purl.obolibrary.org/obo/NCBITaxon_9606 denotes human
T78 586-591 http://purl.obolibrary.org/obo/CLO_0007836 denotes mouse
T79 671-672 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T80 740-750 http://purl.obolibrary.org/obo/CL_0000000 denotes cell types

LitCovid-PD-CHEBI

Id Subject Object Predicate Lexical cue chebi_id
T10 200-207 Chemical denotes protein http://purl.obolibrary.org/obo/CHEBI_36080

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T44 0-228 Sentence denotes In order to assess the veracity of these conceptual associations derived from biomedical literature, it is absolutely essential to enable triangulation with structured data sources including gene and protein expression datasets.
T45 229-617 Sentence denotes To address this need and empower the scientific community, we built a Single Cell RNA-seq (scRNAseq) resource (https://academia.nferx.com/) which harnesses these local and global score metrics to enable seamless integration of literature-derived associations with the analysis of transcriptomes from over 2.2 million individual cells from over 50 human and mouse tissue-types (Figure 1B).
T46 618-906 Sentence denotes Here, we use this first-in-class resource to conduct a comprehensive expression profiling of ACE2 across host tissues and cell types and discuss how the observed expression patterns correlate with the pathogenicity and viral transmission shaping the ongoing COVID-19 pandemic (Figure 1C).