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HypertenGene: extracting key hypertension genes from biomedical literature with position and automatically-generated template features

机译:HypertenGene:从位置和自动生成的模板特征的生物医学文献中提取关键的高血压基因

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摘要

BackgroundThe genetic factors leading to hypertension have been extensively studied, and large numbers of research papers have been published on the subject. One of hypertension researchers' primary research tasks is to locate key hypertension-related genes in abstracts. However, gathering such information with existing tools is not easy: (1) Searching for articles often returns far too many hits to browse through. (2) The search results do not highlight the hypertension-related genes discovered in the abstract. (3) Even though some text mining services mark up gene names in the abstract, the key genes investigated in a paper are still not distinguished from other genes. To facilitate the information gathering process for hypertension researchers, one solution would be to extract the key hypertension-related genes in each abstract. Three major tasks are involved in the construction of this system: (1) gene and hypertension named entity recognition, (2) section categorization, and (3) gene-hypertension relation extraction.
机译:背景技术导致高血压的遗传因素已被广泛研究,有关该主题的大量研究论文也已发表。高血压研究人员的主要研究任务之一是在摘要中定位与高血压相关的关键基因。但是,使用现有工具收集此类信息并不容易:(1)搜索文章通常会返回太多的命中结果,无法浏览。 (2)搜索结果未突出摘要中发现的与高血压相关的基因。 (3)尽管某些文本挖掘服务在摘要中标记了基因名称,但论文中研究的关键基因仍无法与其他基因区分开。为了促进高血压研究人员的信息收集过程,一种解决方案是在每个摘要中提取与高血压相关的关键基因。该系统的构建涉及三个主要任务:(1)基因和高血压,称为实体识别;(2)切片分类;以及(3)基因-高血压关系提取。

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