This example workflow shows how ontology terms can be used to tag biomedical literature.
In the first step, the Triple File Reader node reads an ontology in RDF format (extracted from UniProt) and allows the user to select a disease (using the Autocomplete Text Widget node).
Then, abstracts from PubMed for the specified disease are automatically extracted.
Additionally, a connection to the UniProt SPARQL Endpoint is made and a SPARQL Query executed that allows to extract preferred gene names and disease annotations of all human UniProt entries that are known to be involved in a disease. The gene names are used as the input for the Dictionary Tagger together with the extracted documents from PubMed.
In the last step a component allows to inspect the tagged data.
Note: To open the interactive view of the "View" component do a right click and select "Interactive View".
URL: UniProt SPARQL Endpoint https://sparql.uniprot.org
URL: UniProt Human Diseases in which proteins are involved https://www.uniprot.org/diseases/
To use this workflow in KNIME, download it from the below URL and open it in KNIME:
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