CLC number: Q522
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2019-04-28
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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.
@article{title="Genomic data mining for functional annotation of human long noncoding RNAs",
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",
number="6",
pages="476-487",
year="2019",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.B1900162"
}
%0 Journal Article
%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
%V 20
%N 6
%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
A1 - Brian L. Gudenas
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
IS - 6
SP - 476
EP - 487
%@ 1673-1581
Y1 - 2019
PB - Zhejiang University Press & Springer
ER -
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.
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