Construction of knowledge graph toward immunotherapy
We employed data mining techniques to collect and compile 240 targets of immunotherapy and systematic immunity from the PubMed database. Next, we collected and compiled 345 herbal drug entities officially released by the National Health Commission of China and the National Administration of Traditional Chinese Medicine. The intricate relations between the herbal drug entities and the immunotherapy targets were extracted from the PubMed database. These intricate relations were subjected to further manual curation. We used 13 ontology terms to describe the intricate relations (edges) in the knowledge graph. Moreover, 64 attributes of the medicinal properties for the herbal drug entities were collected and compiled from the Pharmacopoeia of China. Finally, we built the knowledge graph using Neo4j and Py2Neo tools that consists of 895 nodes and 2197 edges.