基于SPO语义三元组的自闭症谱系障碍药物知识发现OACSTPCD

Objective:To extract SPO(Subject-Predicate-Object,SPO)from literature related to Autism Spectrum Disorders(ASD)using semantic mining technology and construct a knowledge graph of ASD drug entities,to explore the potential drug for the treatment of ASD at a deeper level,and provide new ideas for discovering valuable potential drugs for other diseases(https://clinicaltrials.gov).Methods:Using the tools SemRep and Metamap based on the Unified Medical Language System(ULMS)to process ASD literature records and obtain SPO of ASD drug entities.The Neo4j database was used for knowledge storage to construct an ASD drug entities knowledge graph.Using three semantic pathways to discovery ASD drug knowledge based on the knowledge graph.Then verified and analyzed the effectiveness of the results in the clinical trials databases.Results:The SPO obtained includes 1 262 head entities,687 tail entities,and 18 entity relationships.A total of 32 drugs were discovered through three semantic pathways,27 potential drugs for ASD was screened out,and 19 drugs can be validated in the clinical trials databases.Conclusions:The knowledge discovery of ASD drugs based on knowledge graph which built by SPO can provide a certain theoretical and methodological basis for drug repositioning,provide new ideas for traditional drug discovery,and provide decision support for clinical experiments and scientific research.