Text mining effectively scores and ranks the literature for improving chemical-gene-disease curation at the comparative toxicogenomics database.
Text mining effectively scores and ranks the literature for improving chemical-gene-disease curation at the comparative toxicogenomics database.
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DOI：
10.1371/journal.pone.0058201
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发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Mattingly CJ
中科院分区：
文献类型：
--
作者：
Davis AP;Wiegers TC;Johnson RJ;Lay JM;Lennon-Hopkins K;Saraceni-Richards C;Sciaky D;Murphy CG;Mattingly CJ
比较毒理基因组学数据库(CTD；http://ctdbase.org/))是一个公共资源，管理环境化学品和基因产品之间的相互作用，以及它们与疾病的关系，以此作为了解环境化学品对人类健康影响的一种手段。CTD以化学-基因、化学-疾病和基因-疾病相互作用的形式提供了三种核心信息，这些信息是从科学文章中手动挑选出来的。为了提高人工整理的效率、生产力和数据覆盖率，我们利用文本挖掘来帮助对分类文献进行排序和优先排序。在这里，我们描述了我们的文本挖掘过程，该过程计算并为每篇文章分配一个文档相关性分数(DRS)，其中较高的DRS表明一篇文章更有可能与CTD的管理相关。我们通过首先对14,904篇文章的语料库进行文本挖掘来评估我们的过程，这些文章对七种重金属(镉、钴、铜、铅、锰、汞和镍)进行了分类。根据初步分析，然后从14,094篇文章中选择了具有代表性的3,583篇文章子集语料库，并将其发送给五个CTD生物统计人员进行审查。对这3,583篇文章的精选结果进行了各种参数的分析，包括文章相关性、新数据内容、相互作用产率、平均精确度以及生物学和毒理学可解释性。我们表明，对于所有测量的参数，DRS是一个有效的指标，用于对CTD化学基因疾病信息的管理文献进行评分和提高排名。在这里，我们展示了如何将基于文本挖掘的DRS评分完全整合到我们的精选流程中，通过对更相关的文章进行优先排序来增强手动精选，从而提高数据内容、生产力和效率。
The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) is a public resource that curates interactions between environmental chemicals and gene products, and their relationships to diseases, as a means of understanding the effects of environmental chemicals on human health. CTD provides a triad of core information in the form of chemical-gene, chemical-disease, and gene-disease interactions that are manually curated from scientific articles. To increase the efficiency, productivity, and data coverage of manual curation, we have leveraged text mining to help rank and prioritize the triaged literature. Here, we describe our text-mining process that computes and assigns each article a document relevancy score (DRS), wherein a high DRS suggests that an article is more likely to be relevant for curation at CTD. We evaluated our process by first text mining a corpus of 14,904 articles triaged for seven heavy metals (cadmium, cobalt, copper, lead, manganese, mercury, and nickel). Based upon initial analysis, a representative subset corpus of 3,583 articles was then selected from the 14,094 articles and sent to five CTD biocurators for review. The resulting curation of these 3,583 articles was analyzed for a variety of parameters, including article relevancy, novel data content, interaction yield rate, mean average precision, and biological and toxicological interpretability. We show that for all measured parameters, the DRS is an effective indicator for scoring and improving the ranking of literature for the curation of chemical-gene-disease information at CTD. Here, we demonstrate how fully incorporating text mining-based DRS scoring into our curation pipeline enhances manual curation by prioritizing more relevant articles, thereby increasing data content, productivity, and efficiency.
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影响因子：
14.9
作者：
Davis AP;Murphy CG;Saraceni-Richards CA;Rosenstein MC;Wiegers TC;Mattingly CJ
通讯作者：
Mattingly CJ
影响因子：
3
作者：
Van Auken K;Jaffery J;Chan J;Müller HM;Sternberg PW
通讯作者：
Sternberg PW
影响因子：
64.8
作者：
Howe, Doug;Costanzo, Maria;Fey, Petra;Gojobori, Takashi;Hannick, Linda;Hide, Winston;Hill, David P.;Kania, Renate;Schaeffer, Mary;St Pierre, Susan;Twigger, Simon;White, Owen;Rhee, Seung Yon
通讯作者：
Rhee, Seung Yon
影响因子：
9.8
作者：
Rebholz-Schuhmann D;Kirsch H;Couto F
通讯作者：
Couto F
DOI：
10.1093/database/bar065
发表时间：
2012
期刊：
Database : the journal of biological databases and curation
影响因子：
--
作者：
Davis AP;Wiegers TC;Rosenstein MC;Mattingly CJ
通讯作者：
Mattingly CJ