基于SPO語(yǔ)義三元組的自閉癥譜系障礙藥物知識(shí)發(fā)現(xiàn)

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Drug knowledge discovery for autism spectrum disorders based on SPO predications

LYU Yanhua， ZHAO Hongxia， LI Qi， LIANG Aoxue， YU Qi

School of Management， Shanxi Medical University， Shanxi 030001 China

Corresponding Author  LYU Yanhua， E?mail：lvyanhua01@163.com

Abstract  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.

Keywords    autism spectrum disorders； knowledge graph； semantic mining； drug repositioning

摘要  目的：運(yùn)用語(yǔ)義挖掘技術(shù)抽取自閉癥相關(guān)文獻(xiàn)中的三元組并構(gòu)建自閉癥藥物實(shí)體知識(shí)圖譜，深層次開展自閉癥治療的潛力藥物知識(shí)發(fā)現(xiàn)，同時(shí)也為其他疾病發(fā)現(xiàn)有價(jià)值的潛在治療藥物提供新思路。（剩余13353字）