CALBC RDF Triple Store：检索大量文献内容
The CALBC RDF Triple Store: retrieval over large literature content
摘要：
将科学文献整合到生物医学研究基础设施中需要处理文献，识别所包含的命名实体（NE）和概念，并以标准化的方式表示内容。CALBC项目合作伙伴（PP）通过协调自动文本挖掘解决方案（Silver Standard Corpus，SSC）的注释，制作了具有四个不同语义组的大规模注释生物医学语料库。这四个语义组是化学实体和药物（CHED），基因和蛋白质（PRGE），疾病和障碍（DISO）和物种（SPE）。SSC的内容已完全集成到RDF Triple Store（4，568，678个三重）中，并与GeneAtlas（182，840个三重）、UniProtKb（人类12，552，239个三重）和词汇资源LexEBI（BioLexicon）的内容保持一致。RDF Triple Store允许同时查询科学文献和生物信息学资源，以获得遗传原因的证据，例如药物靶点和疾病参与。
英文摘要：
Integration of the scientific literature into a biomedical research infrastructure requires the processing of the literature, identification of the contained named entities (NEs) and concepts, and to represent the content in a standardised way. The CALBC project partners (PPs) have produced a large-scale annotated biomedical corpus with four different semantic groups through the harmonisation of annotations from automatic text mining solutions (Silver Standard Corpus, SSC). The four semantic groups were chemical entities and drugs (CHED), genes and proteins (PRGE), diseases and disorders (DISO) and species (SPE). The content of the SSC has been fully integrated into RDF Triple Store (4,568,678 triples) and has been aligned with content from the GeneAtlas (182,840 triples), UniProtKb (12,552,239 triples for human) and the lexical resource LexEBI (BioLexicon). RDF Triple Store enables querying the scientific literature and bioinformatics resources at the same time for evidence of genetic causes, such as drug targets and disease involvement.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
