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学科主题医学信息学
Computational prediction of associations between long non-coding RNAs and proteins
Lu, Qiongshi1,2,3; Ren, Sijin1,4; Lu, Ming1; Zhang, Yong5; Zhu, Dahai5; Zhang, Xuegong2,3; Li, Tingting1,4
关键词Long non-coding RNA RNA-protein interaction Computation
刊名BMC GENOMICS
2013-09-24
DOI10.1186/1471-2164-14-651
14期:0
收录类别SCI
文章类型Article
WOS标题词Science & Technology
类目[WOS]Biotechnology & Applied Microbiology ; Genetics & Heredity
资助者National Basic Research Program ; National High-tech R& ; D Program of China ; National Natural Science Foundation of China ; National Basic Research Program ; National High-tech R& ; D Program of China ; National Natural Science Foundation of China
研究领域[WOS]Biotechnology & Applied Microbiology ; Genetics & Heredity
关键词[WOS]AMINO-ACID-SEQUENCE ; DOSAGE COMPENSATION ; SECONDARY-STRUCTURE ; X-CHROMOSOME ; HUMAN-CELLS ; EVOLUTION ; DROSOPHILA ; GENE ; ROX1
英文摘要

Background: Though most of the transcripts are long non-coding RNAs (lncRNAs), little is known about their functions. lncRNAs usually function through interactions with proteins, which implies the importance of identifying the binding proteins of lncRNAs in understanding the molecular mechanisms underlying the functions of lncRNAs. Only a few approaches are available for predicting interactions between lncRNAs and proteins. In this study, we introduce a new method lncPro.

Results: By encoding RNA and protein sequences into numeric vectors, we used matrix multiplication to score each RNA-protein pair. This score can be used to measure the interactions between an RNA-protein pair. This method effectively discriminates interacting and non-interacting RNA-protein pairs and predicts RNA-protein interactions within a given complex. Applying this method on all human proteins, we found that the long non-coding RNAs we collected tend to interact with nuclear proteins and RNA-binding proteins.

Conclusions: Compared with the existing approaches, our method shortens the time for training matrix and obtains optimal results based on the model being used. The ability of predicting the associations between lncRNAs and proteins has also been enhanced. Our method provides an idea on how to integrate different information into the prediction process.

语种英语
所属项目编号2011CBA01104 ; 2012CB316504 ; 2012AA020401 ; 31371337 ; 31030041
资助者National Basic Research Program ; National High-tech R& ; D Program of China ; National Natural Science Foundation of China ; National Basic Research Program ; National High-tech R& ; D Program of China ; National Natural Science Foundation of China
WOS记录号WOS:000326171900001
引用统计
被引频次:33[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/400002259/65967
专题基础医学院_医学信息学系
作者单位1.Peking Univ, Hlth Sci Ctr, Sch Basic Med Sci, Dept Biomed Informat, Beijing 100191, Peoples R China
2.Tsinghua Univ, TNLIST Dept Automat, MOE Key Lab Bioinformat, Beijing 100084, Peoples R China
3.Tsinghua Univ, TNLIST Dept Automat, Bioinformat Div, Beijing 100084, Peoples R China
4.Peking Univ, Sch Basic Med Sci, Hlth Sci Ctr, Inst Syst Biomed, Beijing 100191, Peoples R China
5.Chinese Acad Med Sci, Peking Union Med Coll, Sch Basic Med, Natl Lab Med Mol Biol,Inst Basic Med Sci, Beijing 100730, Peoples R China
推荐引用方式
GB/T 7714
Lu, Qiongshi,Ren, Sijin,Lu, Ming,et al. Computational prediction of associations between long non-coding RNAs and proteins[J]. BMC GENOMICS,2013,14(0).
APA Lu, Qiongshi.,Ren, Sijin.,Lu, Ming.,Zhang, Yong.,Zhu, Dahai.,...&Li, Tingting.(2013).Computational prediction of associations between long non-coding RNAs and proteins.BMC GENOMICS,14(0).
MLA Lu, Qiongshi,et al."Computational prediction of associations between long non-coding RNAs and proteins".BMC GENOMICS 14.0(2013).
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