Abstract
BackgroundSemantic web technology has been applied widely in the biomedical informatics field. Large numbers of biomedical datasets are available online in the resource description framework (RDF) format. Semantic relationship mining among genes, disorders, and drugs is widely used in, for example, precision medicine and drug repositioning. However, most of the existing studies focused on a single dataset. It is not easy to find the most current relationships among disorder-gene-drug relationships since the relationships are distributed in heterogeneous datasets. How to mine their semantic relationships from different biomedical datasets is an important issue.MethodsFirst, a variety of biomedical datasets were converted into RDF triple data; then, multisource biomedical datasets were integrated into a storage system using a data integration algorithm. Second, nine query patterns among genes, disorders, and drugs from different biomedical datasets were designed. Third, the gene-disorder-drug semantic relationship mining algorithm is presented. This algorithm can query the relationships among various entities from different datasets.Results and conclusionsWe focused on mining the putative and the most current disorder-gene-drug relationships about Parkinson’s disease (PD). The results demonstrate that our method has significant advantages in mining and integrating multisource heterogeneous biomedical datasets. Twenty-five new relationships among the genes, disorders, and drugs were mined from four different datasets. The query results showed that most of them came from different datasets. The precision of the method increased by 2.51% compared to that of the multisource linked open data fusion method presented in the 4th International Workshop on Semantics-Powered Data Mining and Analytics (SEPDA 2019). Moreover, the number of query results increased by 7.7%, and the number of correct queries increased by 9.5%.
Highlights
Semantic web technology has been applied widely in the biomedical informatics field
Twenty-five new relationships among the genes, disorders, and drugs were mined from four different datasets
The query results showed that most of them came from different datasets
Summary
Semantic web technology has been applied widely in the biomedical informatics field. Large numbers of biomedical datasets are available online in the resource description framework (RDF) format. It is not easy to find the most current relationships among disorder-gene-drug relationships since the relationships are distributed in heterogeneous datasets How to mine their semantic relationships from different biomedical datasets is an important issue. A uniform resource identifier (URI) and character strings are used to represent different entities and the relationships between entities These semantic datasets are published online and can be accessed via the HTTP protocol and are known as linked open datasets [1]. The Life Sciences dataset is one of the most important parts of Linked Open Data Cloud [2] This database consists of 339 RDF datasets, including 234 BioPortal datasets, 35 Bio2RDF datasets, and 70 other datasets.
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