ATOM: Construction of Anti-tumor Biomaterial Knowledge Graph by Biomedicine Literature

With the rapid development of anti-tumor biomaterials, biomedicine literature with respect to anti-tumor biomaterials has been leveraged for tumor treatment as it provides abundant and useful information. A large number of biomedicine literature contains unstructured data, making it difficult for researchers to obtain desired messages from it. Knowledge Graphs (KGs) provides structured relationships among entities and can be served as a solution. However, no existing tool can be found in constructing an anti-tumor biomaterial knowledge graph from biomedicine literature. To fill this gap, a novel approach, ATOM, was proposed to construct an anti-tumor biomaterial knowledge graph from biomedicine literature through a series of process including the recognition of anti-tumor entities, the simplification of sentences, the extraction of triples, and the predicate mapping. Experiments demonstrated that ATOM is able to effectively express the extracted anti-tumor entities and their relationships.