生物医学文献中蛋白质关联的发现

Yueyu Fu, Javed Mostafa, Kazuhiro Seki
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引用次数: 10

摘要

蛋白质关联的发现可以直接促进蛋白质通路的发展;因此,它是生物信息学中的一个重要问题。LUCAS(面向用户的访问服务概念库)设计用于从生物医学文献中自动提取和确定蛋白质之间的关联。该工具具有显著的潜力,可以实现生物医学数据库的自动化建设,而不是依赖于专家的分析。我们报告了自动生成蛋白质簇的机制。基于2000个MEDLINE标题和摘要的子集,对该系统进行了正式评估,并对Swiss-Prot数据库进行了评估,其中概念之间的关联由专家手动输入。
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Protein association discovery in biomedical literature
Protein association discovery can directly contribute toward developing protein pathways; hence it is a significant problem in bioinformatics. LUCAS (Library of User-Oriented Concepts for Access Services) was designed to automatically extract and determine associations among proteins from biomedical literature. Such a tool has notable potential to automate database construction in biomedicine, instead of relying on experts' analysis. We report on the mechanisms for automatically generating clusters of proteins. A formal evaluation of the system, based on a subset of 2000 MEDLINE titles and abstracts, has been conducted against Swiss-Prot database in which the associations among concepts are entered by experts manually.
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