ALIBABA: PubMed as a graph
ALIBABA: PubMed as a graph
复制标题
DOI：
10.1093/bioinformatics/btl408
复制
发表时间：
2006-10-01
期刊：
影响因子：
5.8
通讯作者：
Leser, Ulf
中科院分区：
文献类型：
--
作者：
Plake, Conrad;Schiemann, Torsten;Leser, Ulf
生物医学文献包含了大量关于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 - 疾病关联以及蛋白质的亚细胞定位。当使用常规搜索引擎（例如PubMed）搜索此类信息时，用户一次只能看到一篇摘要中的数据，而且这些数据“隐藏”在自然语言文本中。AliBaba是一种用于对搜索结果进行图形化总结的交互工具。它解析符合PubMed查询的一组摘要，并将提取的关于生物医学对象及其关系的信息呈现为一个图形网络。AliBaba提取细胞、疾病、药物、蛋白质、物种和组织之间的关联。若干筛选选项允许进行更有针对性的搜索。因此，研究人员可以一眼就掌握各种文章中描述的复杂网络。
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.