CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
Institute of Environmental Engineering, ETH Zurich, Zurich 8093, Switzerland.
Bioinformatics. 2023 Jul 1;39(7). doi: 10.1093/bioinformatics/btad440.
Despite low prevalence, rare diseases affect 300 million people worldwide. Research on pathogenesis and drug development lags due to limited commercial potential, insufficient epidemiological data, and a dearth of publications. The unique characteristics of rare diseases, including limited annotated data, intricate processes for extracting pertinent entity relationships, and difficulties in standardizing data, represent challenges for text mining.
We developed a rare disease data acquisition framework using text mining and knowledge graphs and constructed the most comprehensive rare disease knowledge graph to date, Rare Disease Bridge (RDBridge). RDBridge offers search functions for genes, potential drugs, pathways, literature, and medical imaging data that will support mechanistic research, drug development, diagnosis, and treatment for rare diseases.
RDBridge is freely available at http://rdb.lifesynther.com/.
尽管罕见病的患病率较低，但全球仍有 3 亿人受到其影响。由于商业潜力有限、流行病学数据不足以及出版物匮乏，罕见病的发病机制研究和药物开发较为滞后。罕见病的独特特征，包括有限的注释数据、提取相关实体关系的复杂过程以及数据标准化的困难，给文本挖掘带来了挑战。
我们利用文本挖掘和知识图谱开发了一种罕见病数据获取框架，并构建了迄今为止最全面的罕见病知识图谱，即罕见病桥梁（RDBridge）。RDBridge 提供了针对基因、潜在药物、途径、文献和医学成像数据的搜索功能，这将支持罕见病的机制研究、药物开发、诊断和治疗。
RDBridge 可在 http://rdb.lifesynther.com/ 免费获取。
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