miRiaD: A Text Mining Tool for Detecting Associations of microRNAs with Diseases.
miRiaD: A Text Mining Tool for Detecting Associations of microRNAs with Diseases.
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DOI：
10.1186/s13326-015-0044-y
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发表时间：
2016-04-29
影响因子：
1.9
通讯作者：
Vijay-Shanker K
中科院分区：
文献类型：
--
作者：
Gupta S;Ross KE;Tudor CO;Wu CH;Schmidt CJ;Vijay-Shanker K
microRNA作为人类疾病的关键参与者越来越受到重视，有关microRNA作用的问题在生物医学研究的许多领域出现。有几个从生物医学文献中收集的microRNA-疾病关联的人工策划数据库;然而，这些数据库的策展人很难跟上microRNA-疾病领域出版物的爆炸。此外，帮助手动管理microRNA-疾病关联的自动化文献挖掘工具目前仅捕获一种疾病（癌症）背景下的一种microRNA特性（表达）。因此，显然需要开发更复杂的自动化文献挖掘工具，以捕获多种疾病背景下的各种microRNA特性和关系，为研究人员提供快速访问最新发布的信息，并简化和加速人工管理。我们开发了miRiaD（microRNAs in association with Disease），这是一种文本挖掘工具，可以自动从文献中提取microRNAs与疾病之间的关联。这些协会往往没有直接联系，和中间关系往往是高度信息的生物医学研究人员。因此，miRiaD提取了miR-疾病对以及对其关联的解释。我们还开发了一种程序，根据句子中观察到的微RNA与疾病的关系，为句子打分，标记它们的信息量。将miRiaD应用于整个Medline语料库，识别出8301个具有miR-疾病关联的PMID。这些摘要和miR-疾病关联可在http://biotm.cis.udel.edu/miRiaD上浏览。我们评估了miRiaD在公共microRNA疾病数据库管理员高度感兴趣的信息（表达和靶基因关联）方面的召回率和精确度，获得了88.46-90.78的召回率。当我们将评估扩展到包含生物医学研究人员可能感兴趣的各种微RNA疾病信息的句子时，miRiaD也表现得非常好，F分数为89.4。句子的信息量排名进行了评估，在nDCG（0.977）和相关性指标（0.678-0.727）相比，注释者的排名列表。miRiaD是一种高性能系统，可以捕获各种microRNA疾病相关信息，超出了现有microRNA疾病资源的范围。它可以被纳入手动管理管道，并作为对microRNA在疾病中的作用感兴趣的生物医学研究人员的资源。在我们正在进行的工作中，我们正在开发一个改进的miRiaD网络界面，这将有助于有关microRNA-疾病关系的复杂查询，例如“在哪些疾病中microRNA对细胞凋亡的调节起作用？”或者“在不同类型的痴呆症中，microRNA靶向的基因组是否存在重叠？”本文的在线版本（doi：10.1186/s13326-015-0044-y）包含补充材料，可供授权用户使用。
MicroRNAs are increasingly being appreciated as critical players in human diseases, and questions concerning the role of microRNAs arise in many areas of biomedical research. There are several manually curated databases of microRNA-disease associations gathered from the biomedical literature; however, it is difficult for curators of these databases to keep up with the explosion of publications in the microRNA-disease field. Moreover, automated literature mining tools that assist manual curation of microRNA-disease associations currently capture only one microRNA property (expression) in the context of one disease (cancer). Thus, there is a clear need to develop more sophisticated automated literature mining tools that capture a variety of microRNA properties and relations in the context of multiple diseases to provide researchers with fast access to the most recent published information and to streamline and accelerate manual curation. We have developed miRiaD (microRNAs in association with Disease), a text-mining tool that automatically extracts associations between microRNAs and diseases from the literature. These associations are often not directly linked, and the intermediate relations are often highly informative for the biomedical researcher. Thus, miRiaD extracts the miR-disease pairs together with an explanation for their association. We also developed a procedure that assigns scores to sentences, marking their informativeness, based on the microRNA-disease relation observed within the sentence. miRiaD was applied to the entire Medline corpus, identifying 8301 PMIDs with miR-disease associations. These abstracts and the miR-disease associations are available for browsing at http://biotm.cis.udel.edu/miRiaD. We evaluated the recall and precision of miRiaD with respect to information of high interest to public microRNA-disease database curators (expression and target gene associations), obtaining a recall of 88.46–90.78. When we expanded the evaluation to include sentences with a wide range of microRNA-disease information that may be of interest to biomedical researchers, miRiaD also performed very well with a F-score of 89.4. The informativeness ranking of sentences was evaluated in terms of nDCG (0.977) and correlation metrics (0.678-0.727) when compared to an annotator’s ranked list. miRiaD, a high performance system that can capture a wide variety of microRNA-disease related information, extends beyond the scope of existing microRNA-disease resources. It can be incorporated into manual curation pipelines and serve as a resource for biomedical researchers interested in the role of microRNAs in disease. In our ongoing work we are developing an improved miRiaD web interface that will facilitate complex queries about microRNA-disease relationships, such as “In what diseases does microRNA regulation of apoptosis play a role?” or “Is there overlap in the sets of genes targeted by microRNAs in different types of dementia?”.” The online version of this article (doi:10.1186/s13326-015-0044-y) contains supplementary material, which is available to authorized users.