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ALIBABA: PubMed as a graph

机译:阿里巴巴:PubMed作为图表

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摘要

The biomedical literature contains a wealth of information on associations between many different types of objects, such as protein-protein interactions, gene-disease associations and subcellular locations of proteins. When searching such information using conventional search engines, e.g. PubMed, users see the data only one-abstract at a time and 'hidden' in natural language text. AliBaba is an interactive tool for graphical summarization of search results. It parses the set of abstracts that fit a PubMed query and presents extracted information on biomedical objects and their relationships as a graphical network. AliBaba extracts associations between cells, diseases, drugs, proteins, species and tissues. Several filter options allow for a more focused search. Thus, researchers can grasp complex networks described in various articles at a glance.
机译:生物医学文献包含许多有关许多不同类型对象之间关联的信息,例如蛋白质-蛋白质相互作用,基因-疾病关联和蛋白质的亚细胞位置。当使用常规搜索引擎搜索此类信息时,例如在PubMed中,用户一次只能看到一个摘要的数据,而在自然语言文本中则是“隐藏”的。 AliBaba是一种用于对搜索结果进行图形汇总的交互式工具。它解析适合PubMed查询的摘要集,并将有关生物医学对象及其关系的提取信息呈现为图形网络。 AliBaba提取细胞,疾病,药物,蛋白质,物种和组织之间的关联。几个过滤器选项使搜索更加集中。因此,研究人员可以一眼掌握各种文章中描述的复杂网络。

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