Abstract
BackgroundStroke has an acute onset and a high mortality rate, making it one of the most fatal diseases worldwide. Its underlying biology and treatments have been widely studied both in the “Western” biomedicine and the Traditional Chinese Medicine (TCM). However, these two approaches are often studied and reported in insolation, both in the literature and associated databases.ResultsTo aid research in finding effective prevention methods and treatments, we integrated knowledge from the literature and a number of databases (e.g. CID, TCMID, ETCM). We employed a suite of biomedical text mining (i.e. named-entity) approaches to identify mentions of genes, diseases, drugs, chemicals, symptoms, Chinese herbs and patent medicines, etc. in a large set of stroke papers from both biomedical and TCM domains. Then, using a combination of a rule-based approach with a pre-trained BioBERT model, we extracted and classified links and relationships among stroke-related entities as expressed in the literature. We construct StrokeKG, a knowledge graph includes almost 46 k nodes of nine types, and 157 k links of 30 types, connecting diseases, genes, symptoms, drugs, pathways, herbs, chemical, ingredients and patent medicine.ConclusionsOur Stroke-KG can provide practical and reliable stroke-related knowledge to help with stroke-related research like exploring new directions for stroke research and ideas for drug repurposing and discovery. We make StrokeKG freely available at http://114.115.208.144:7474/browser/ (Please click "Connect" directly) and the source structured data for stroke at https://github.com/yangxi1016/Stroke
Highlights
Stroke has an acute onset and a high mortality rate, making it one of the most fatal diseases worldwide
We aim to develop a stroke-related knowledge base by combining information extracted from these scientific papers and existing knowledge bases
In this paper we introduce a stroke-related knowledge graph (StrokeKG) by combining information extracted from these scientific papers and existing knowledge bases
Summary
Stroke has an acute onset and a high mortality rate, making it one of the most fatal diseases worldwide. Its underlying biology and treatments have been widely studied both in the “Western” biomedicine and the Traditional Chinese Medicine (TCM). These two approaches are often studied and reported in insolation, both in the literature and associated databases. Yang et al BMC Bioinformatics (2021) 22:387 particular in declining stroke mortality [2] Western therapeutic such as drug injection and endovascular therapy [3], as well as traditional Chinese treatment such as herbal medicine and acupuncture [4], have made tremendous efforts for preventing stroke and recovery after stroke. We aim to develop a stroke-related knowledge base by combining information extracted from these scientific papers and existing knowledge bases. The large volume of texts requires automated and computational methods to extract useful information from these unstructured data to build structured databases
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