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学科主题医学信息学
A Computational Framework to Infer Human Disease-Associated Long Noncoding RNAs
Liu, Ming-Xi1,2; Chen, Xing1,3; Chen, Geng4; Cui, Qing-Hua4; Yan, Gui-Ying1,3
刊名PLOS ONE
2014-01-02
DOI10.1371/journal.pone.0084408
9期:1
收录类别SCI
文章类型Article
WOS标题词Science & Technology
类目[WOS]Multidisciplinary Sciences
资助者National Natural Science Foundation of China ; National Center for Mathematics and Interdisciplinary Sciences, CAS ; National Natural Science Foundation of China ; National Center for Mathematics and Interdisciplinary Sciences, CAS
研究领域[WOS]Science & Technology - Other Topics
关键词[WOS]GENE-EXPRESSION ; BREAST-CANCER ; DATABASE ; GENOME ; PROTEIN ; INHIBITOR ; MOUSE ; OVEREXPRESSION ; SUSCEPTIBILITY ; IDENTIFICATION
英文摘要

As a major class of noncoding RNAs, long noncoding RNAs (lncRNAs) have been implicated in various critical biological processes. Accumulating researches have linked dysregulations and mutations of lncRNAs to a variety of human disorders and diseases. However, to date, only a few human lncRNAs have been associated with diseases. Therefore, it is very important to develop a computational method to globally predict potential associated diseases for human lncRNAs. In this paper, we developed a computational framework to accomplish this by combining human lncRNA expression profiles, gene expression profiles, and human disease-associated gene data. Applying this framework to available human long intergenic noncoding RNAs (lincRNAs) expression data, we showed that the framework has reliable accuracy. As a result, for non-tissue-specific lincRNAs, the AUC of our algorithm is 0.7645, and the prediction accuracy is about 89%. This study will be helpful for identifying novel lncRNAs for human diseases, which will help in understanding the roles of lncRNAs in human diseases and facilitate treatment. The corresponding codes for our method and the predicted results are all available at http://asdcd.amss.ac.cn/MingXiLiu/lncRNA-disease.html.

语种英语
所属项目编号10531070 ; 10721101 ; 11301517 ; 11371355 ; KJCX-YW-S7
资助者National Natural Science Foundation of China ; National Center for Mathematics and Interdisciplinary Sciences, CAS ; National Natural Science Foundation of China ; National Center for Mathematics and Interdisciplinary Sciences, CAS
WOS记录号WOS:000329460100056
引用统计
被引频次:36[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
版本出版稿
条目标识符http://ir.bjmu.edu.cn/handle/400002259/64808
专题基础医学院_医学信息学系
作者单位1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
3.Chinese Acad Sci, Ctr Math & Interdisciplinary Sci, Beijing, Peoples R China
4.Peking Univ, Sch Basic Med Sci, Dept Biomed Informat, Beijing 100871, Peoples R China
推荐引用方式
GB/T 7714
Liu, Ming-Xi,Chen, Xing,Chen, Geng,et al. A Computational Framework to Infer Human Disease-Associated Long Noncoding RNAs[J]. PLOS ONE,2014,9(1).
APA Liu, Ming-Xi,Chen, Xing,Chen, Geng,Cui, Qing-Hua,&Yan, Gui-Ying.(2014).A Computational Framework to Infer Human Disease-Associated Long Noncoding RNAs.PLOS ONE,9(1).
MLA Liu, Ming-Xi,et al."A Computational Framework to Infer Human Disease-Associated Long Noncoding RNAs".PLOS ONE 9.1(2014).
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