Detecting miRNA Mentions and Relations in Biomedical Literature.
Detecting miRNA Mentions and Relations in Biomedical Literature.
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DOI：
10.12688/f1000research.4591.1
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发表时间：
2014-01-01
期刊：
影响因子：
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通讯作者：
Klinger, Roman
中科院分区：
文献类型：
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作者：
Bagewadi, Shweta;Bobic, Tamara;Klinger, Roman
简介：microRNA（miRNAs）作为转录后基因表达调控因子，参与细胞凋亡、分化和应激反应等多种调控过程。除了miRNA在正常生理学中的作用外，它们的失调还涉及大量疾病。对miRNA相关关联的剖析对于思考其在疾病中的机制是有价值的，从而发现用于疾病预后、诊断和治疗的新型miRNA。动机：除了数据库和预测工具之外，miRNA相关信息主要以非结构化文本的形式提供。由于出版物数量的稳步增长，这些关联的手动检索可能是劳动密集型的。尽管事实上，一些数据库托管来自文本的miRNA关联，但较低的敏感性激发了对即兴框架的需求。此外，缺乏一个标准的语料库的miRNA的关系，造成了困难，在评估可用的系统。我们提出的方法，自动提取提到的miRNA，物种，基因/蛋白质，疾病，和科学文献的关系。我们生成的语料库、沿着字典和miRNA正则表达式可免费用于学术目的。结果：识别特异性miRNA的召回率为0.94，准确率为0.93。提取miRNA-疾病和miRNA-基因关系导致高达0.76的F1评分。通过我们的方法提取的信息与用于提取阿尔茨海默病相关关系的数据库miR 2Disease和miRSel的比较显示了我们所提出的方法在识别具有提高的灵敏度的正确关系方面的能力。已发表的资源和描述的方法可以帮助研究人员最大限度地检索miRNA关系和生成miRNA调控网络。可用性：训练和测试语料库，注释指南，开发的词典和补充文件可在http://www.scai.fraunhofer.de/mirna-corpora.html上获得。
INTRODUCTION: MicroRNAs (miRNAs) have demonstrated their potential as post-transcriptional gene expression regulators, participating in a wide spectrum of regulatory events such as apoptosis, differentiation, and stress response. Apart from the role of miRNAs in normal physiology, their dysregulation is implicated in a vast array of diseases. Dissection of miRNA-related associations are valuable for contemplating their mechanism in diseases, leading to the discovery of novel miRNAs for disease prognosis, diagnosis, and therapy.MOTIVATION: Apart from databases and prediction tools, miRNA-related information is largely available as unstructured text. Manual retrieval of these associations can be labor-intensive due to steadily growing number of publications. Despite the fact that several databases host miRNA-associations derived from text, lower sensitivity has motivated the need for an improvised framework. Additionally, the lack of a standard corpus for miRNA-relations has caused difficulty in evaluating the available systems. We propose methods to automatically extract mentions of miRNAs, species, genes/proteins, disease, and relations from scientific literature. Our generated corpora, along with dictionaries, and miRNA regular expression are freely available for academic purposes. To our knowledge, these resources are the most comprehensive developed so far.RESULTS: The identification of specific miRNA mentions reaches a recall of 0.94 and precision of 0.93. Extraction of miRNA-disease and miRNA-gene relations lead to an F 1 score of up to 0.76. A comparison of the information extracted by our approach to the databases miR2Disease and miRSel for the extraction of Alzheimer's disease related relations shows the capability of our proposed methods in identifying correct relations with improved sensitivity. The published resources and described methods can help the researchers for maximal retrieval of miRNA-relations and generation of miRNA-regulatory networks.AVAILABILITY: The training and test corpora, annotation guidelines, developed dictionaries, and supplementary files are available at http://www.scai.fraunhofer.de/mirna-corpora.html.