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PMC:7510993 / 5790-6382 JSONTXT

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LitCovid-PD-FMA-UBERON

Id Subject Object Predicate Lexical cue fma_id
T2 551-556 Body_part denotes cells http://purl.org/sig/ont/fma/fma68646

LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T49 94-102 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T27 514-515 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T28 551-556 http://purl.obolibrary.org/obo/GO_0005623 denotes cells
T29 572-573 http://purl.obolibrary.org/obo/CLO_0001020 denotes a

LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
115 94-102 Disease denotes COVID-19 MESH:C000657245

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T32 0-72 Sentence denotes For each country or region, we compiled several environmental variables.
T33 73-256 Sentence denotes For mapping cases of COVID-19, the longitude and latitude of the largest city and area for each country or region were extracted from GADM maps and data (https://gadm.org/index.html).
T34 257-592 Sentence denotes Based on the geocoordinates of the cities, we collected the climatic data of mean precipitation (mm month–1) and temperature (°C) from January to June (WorldClim) using WorldClim version 2.1 climate data (https://www.worldclim.org/data/worldclim21.html) at a resolution of 2.5 arc-minutes grid cells that contained a country or region.