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CLC number: Q522

On-line Access: 2019-05-15

Received: 2019-03-29

Revision Accepted: 2019-04-15

Crosschecked: 2019-04-28

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Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Liang-Jiang Wang

https://orcid.org/0000-0002-6316-7962

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Journal of Zhejiang University SCIENCE B 2019 Vol.20 No.6 P.476-487

http://doi.org/10.1631/jzus.B1900162


Genomic data mining for functional annotation of human long noncoding RNAs


Author(s):  Brian L. Gudenas, Jun Wang, Shu-Zhen Kuang, An-Qi Wei, Steven B. Cogill, Liang-Jiang Wang

Affiliation(s):  Department of Genetics and Biochemistry, Clemson University, Clemson, South Carolina 29634, USA

Corresponding email(s):   liangjw@clemson.edu

Key Words:  Long noncoding RNA, Functional annotation, Genomic data mining, Machine learning


Brian L. Gudenas, Jun Wang, Shu-Zhen Kuang, An-Qi Wei, Steven B. Cogill, Liang-Jiang Wang. Genomic data mining for functional annotation of human long noncoding RNAs[J]. Journal of Zhejiang University Science B, 2019, 20(6): 476-487.

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author="Brian L. Gudenas, Jun Wang, Shu-Zhen Kuang, An-Qi Wei, Steven B. Cogill, Liang-Jiang Wang",
journal="Journal of Zhejiang University Science B",
volume="20",
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pages="476-487",
year="2019",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.B1900162"
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%T Genomic data mining for functional annotation of human long noncoding RNAs
%A Brian L. Gudenas
%A Jun Wang
%A Shu-Zhen Kuang
%A An-Qi Wei
%A Steven B. Cogill
%A Liang-Jiang Wang
%J Journal of Zhejiang University SCIENCE B
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%P 476-487
%@ 1673-1581
%D 2019
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.B1900162

TY - JOUR
T1 - Genomic data mining for functional annotation of human long noncoding RNAs
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A1 - Jun Wang
A1 - Shu-Zhen Kuang
A1 - An-Qi Wei
A1 - Steven B. Cogill
A1 - Liang-Jiang Wang
J0 - Journal of Zhejiang University Science B
VL - 20
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SP - 476
EP - 487
%@ 1673-1581
Y1 - 2019
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.B1900162


Abstract: 
Life may have begun in an RNA world, which is supported by increasing evidence of the vital role that RNAs perform in biological systems. In the human genome, most genes actually do not encode proteins; they are noncoding RNA genes. The largest class of noncoding genes is known as long noncoding RNAs (lncRNAs), which are transcripts greater in length than 200 nucleotides, but with no protein-coding capacity. While some lncRNAs have been demonstrated to be key regulators of gene expression and 3D genome organization, most lncRNAs are still uncharacterized. We thus propose several data mining and machine learning approaches for the functional annotation of human lncRNAs by leveraging the vast amount of data from genetic and genomic studies. Recent results from our studies and those of other groups indicate that genomic data mining can give insights into lncRNA functions and provide valuable information for experimental studies of candidate lncRNAs associated with human disease.

利用基因组数据挖掘对人类长非编码RNA进行功能注释

概要:越来越多证据表明RNA在生物系统中扮演着重要的角色,而这些发现支持了生命起源于RNA的假设.在人类基因组中,大部分的基因并不编码蛋白质,被称为非编码RNA基因.长非编码RNA(lncRNA)是其中最大的一类,其转录本长度大于200个核苷酸.虽然一些lncRNA已被证明是调控基因表达和3D基因组结构的重要元件,但是大部分lncRNA还未被研究和注释.本课题组利用大量基因组数据,提出一些基于数据挖掘和机器学习的方法,对人类lncRNA进行功能注释.我们与其他同领域课题组的近期研究结果表明,基因组数据挖掘可帮助加深对lncRNA功能的理解,并为与疾病相关lncRNA的实验研究提供重要信息.
关键词:长非编码RNA(lncRNA);功能注释;基因组数据挖掘;机器学习

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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