首页> 外文期刊>Toxicology in vitro: an international journal published in association with BIBRA >Automatic sorting of toxicological information into the IUCLID (International Uniform Chemical Information Database) endpoint-categories making use of the semantic search engine Go3R
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Automatic sorting of toxicological information into the IUCLID (International Uniform Chemical Information Database) endpoint-categories making use of the semantic search engine Go3R

机译:利用语义搜索引擎Go3R将毒理学信息自动分类到IUCLID(国际统一化学信息数据库)端点类别中

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摘要

The knowledge-based search engine Go3R, www.Go3R.org, has been developed to assist scientists from industry and regulatory authorities in collecting comprehensive toxicological information with a special focus on identifying available alternatives to animal testing. The semantic search paradigm of Go3R makes use of expert knowledge on 3Rs methods and regulatory toxicology, laid down in the ontology, a network of concepts, terms, and synonyms, to recognize the contents of documents. Search results are automatically sorted into a dynamic table of contents presented alongside the list of documents retrieved. This table of contents allows the user to quickly filter the set of documents by topics of interest. Documents containing hazard information are automatically assigned to a user interface following the endpoint-specific IUCLID5 categorization scheme required, e.g. for REACH registration dossiers. For this purpose, complex endpoint-specific search queries were compiled and integrated into the search engine (based upon a gold standard of 310 references that had been assigned manually to the different endpoint categories). Go3R sorts 87% of the references concordantly into the respective IUCLID5 categories. Currently, Go3R searches in the 22. million documents available in the PubMed and TOXNET databases. However, it can be customized to search in other databases including in-house databanks.
机译:基于知识的搜索引擎Go3R(www.Go3R.org)的开发旨在帮助行业和监管机构的科学家收集全面的毒理学信息,并特别着重于确定可用于动物实验的替代方法。 Go3R的语义搜索范式利用3Rs方法和监管毒理学方面的专业知识(位于本体,概念,术语和同义词的网络中)来识别文档的内容。搜索结果将自动分类到一个动态目录中,该目录与检索到的文档列表一起显示。此目录使用户可以按感兴趣的主题快速筛选文档集。包含危害信息的文档会按照所需的特定于端点的IUCLID5分类方案自动分配给用户界面。用于REACH注册卷宗。为此,将复杂的特定于端点的搜索查询编译并集成到搜索引擎中(基于310黄金参考标准,该参考标准已手动分配给不同的端点类别)。 Go3R将87%的引用一致地分类到相应的IUCLID5类别中。目前,Go3R在PubMed和TOXNET数据库中可用的2200万份文档中进行搜索。但是,可以对其进行自定义以在其他数据库(包括内部数据库)中进行搜索。

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