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APPLICATION OF AUTOMATIC MUTATION–GENE PAIR EXTRACTION TO DISEASES

机译:自动突变基因对提取在疾病中的应用

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摘要

To have a better understanding of the mechanisms of disease development, knowledge of mutations and the genes on which the mutations occur is of crucial importance. Information on disease-related mutations can be accessed through public databases or biomedical literature sources. However, information retrieval from such resources can be problematic because of two reasons: manually created databases are usually incomplete and not up to date, and reading through a vast amount of publicly available biomedical documents is very time-consuming. In this paper, we describe an automated system, MuGeX (Mutation Gene eXtractor), that automatically extracts mutation–gene pairs from Medline abstracts for a disease query. Our system is tested on a corpus that consists of 231 Medline abstracts. While recall for mutation detection alone is 85.9%, precision is 95.9%. For extraction of mutation–gene pairs, we focus on Alzheimer's disease. The recall for mutation–gene pairidentification is estimated at 91.3%, and precision is estimated at 88.9%. With automatic extraction techniques, MuGeX overcomes the problems of information retrieval from public resources and reduces the time required to access relevant information, while preserving the accuracy of retrieved information.
机译:为了更好地了解疾病的发展机制,了解突变以及发生突变的基因至关重要。可以通过公共数据库或生物医学文献资源获取有关疾病相关突变的信息。但是,由于以下两个原因,从此类资源中检索信息可能会出现问题:手动创建的数据库通常不完整且不是最新的,并且读取大量可公开获得的生物医学文档非常耗时。在本文中,我们描述了一个自动化系统MuGeX(突变基因提取器),该系统从Medline摘要中自动提取突变基因对,以进行疾病查询。我们的系统在包含231个Medline摘要的语料库上进行了测试。虽然仅突变检测的召回率为85.9%,但准确度为95.9%。对于提取突变基因对,我们关注阿尔茨海默氏病。突变基因配对识别的召回率估计为91.3%,准确度估计为88.9%。借助自动提取技术,MuGeX克服了从公共资源检索信息的问题,并减少了访问相关信息所需的时间,同时保留了检索信息的准确性。

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