Literature DB >> 28427142

iRNA-PseU: Identifying RNA pseudouridine sites.

Wei Chen1, Hua Tang2, Jing Ye3, Hao Lin4, Kuo-Chen Chou5.   

Abstract

As the most abundant RNA modification, pseudouridine plays important roles in many biological processes. Occurring at the uridine site and catalyzed by pseudouridine synthase, the modification has been observed in nearly all kinds of RNA, including transfer RNA, messenger RNA, small nuclear or nucleolar RNA, and ribosomal RNA. Accordingly, its importance to basic research and drug development is self-evident. Despite some experimental technologies have been developed to detect the pseudouridine sites, they are both time-consuming and expensive. Facing the explosive growth of RNA sequences in the postgenomic age, we are challenged to address the problem by computational approaches: For an uncharacterized RNA sequence, can we predict which of its uridine sites can be modified as pseudouridine and which ones cannot? Here a predictor called "iRNA-PseU" was proposed by incorporating the chemical properties of nucleotides and their occurrence frequency density distributions into the general form of pseudo nucleotide composition (PseKNC). It has been demonstrated via the rigorous jackknife test, independent dataset test, and practical genome-wide analysis that the proposed predictor remarkably outperforms its counterpart. For the convenience of most experimental scientists, the web-server for iRNA-PseU was established at http://lin.uestc.edu.cn/server/iRNA-PseU, by which users can easily get their desired results without the need to go through the mathematical details.
Copyright © 2016 Official journal of the American Society of Gene & Cell Therapy. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Web-server; iRNA-PseU; nucleotide chemical property; nucleotide frequency; pseudouridine; Ψ site

Year:  2016        PMID: 28427142      PMCID: PMC5330936          DOI: 10.1038/mtna.2016.37

Source DB:  PubMed          Journal:  Mol Ther Nucleic Acids


  77 in total

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Authors:  Zi Liu; Xuan Xiao; Dong-Jun Yu; Jianhua Jia; Wang-Ren Qiu; Kuo-Chen Chou
Journal:  Anal Biochem       Date:  2015-12-31       Impact factor: 3.365

Review 2.  Applications of graph theory to enzyme kinetics and protein folding kinetics. Steady and non-steady-state systems.

Authors:  K C Chou
Journal:  Biophys Chem       Date:  1990-01       Impact factor: 2.352

3.  iDNA-Methyl: identifying DNA methylation sites via pseudo trinucleotide composition.

Authors:  Zi Liu; Xuan Xiao; Wang-Ren Qiu; Kuo-Chen Chou
Journal:  Anal Biochem       Date:  2015-01-14       Impact factor: 3.365

4.  iLoc-Animal: a multi-label learning classifier for predicting subcellular localization of animal proteins.

Authors:  Wei-Zhong Lin; Jian-An Fang; Xuan Xiao; Kuo-Chen Chou
Journal:  Mol Biosyst       Date:  2013-01-31

5.  A vectorized sequence-coupling model for predicting HIV protease cleavage sites in proteins.

Authors:  K C Chou
Journal:  J Biol Chem       Date:  1993-08-15       Impact factor: 5.157

6.  Prediction of β-lactamase and its class by Chou's pseudo-amino acid composition and support vector machine.

Authors:  Ravindra Kumar; Abhishikha Srivastava; Bandana Kumari; Manish Kumar
Journal:  J Theor Biol       Date:  2014-10-22       Impact factor: 2.691

7.  Identification of real microRNA precursors with a pseudo structure status composition approach.

Authors:  Bin Liu; Longyun Fang; Fule Liu; Xiaolong Wang; Junjie Chen; Kuo-Chen Chou
Journal:  PLoS One       Date:  2015-03-30       Impact factor: 3.240

8.  Transcriptome-wide mapping of pseudouridines: pseudouridine synthases modify specific mRNAs in S. cerevisiae.

Authors:  Alexander F Lovejoy; Daniel P Riordan; Patrick O Brown
Journal:  PLoS One       Date:  2014-10-29       Impact factor: 3.240

9.  Some remarks on protein attribute prediction and pseudo amino acid composition.

Authors:  Kuo-Chen Chou
Journal:  J Theor Biol       Date:  2010-12-17       Impact factor: 2.691

10.  CD-HIT: accelerated for clustering the next-generation sequencing data.

Authors:  Limin Fu; Beifang Niu; Zhengwei Zhu; Sitao Wu; Weizhong Li
Journal:  Bioinformatics       Date:  2012-10-11       Impact factor: 6.937

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  76 in total

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Authors:  Kewei Liu; Wei Chen; Hao Lin
Journal:  Mol Genet Genomics       Date:  2019-08-07       Impact factor: 3.291

2.  iPhosY-PseAAC: identify phosphotyrosine sites by incorporating sequence statistical moments into PseAAC.

Authors:  Yaser Daanial Khan; Nouman Rasool; Waqar Hussain; Sher Afzal Khan; Kuo-Chen Chou
Journal:  Mol Biol Rep       Date:  2018-10-11       Impact factor: 2.316

3.  Predicting membrane proteins and their types by extracting various sequence features into Chou's general PseAAC.

Authors:  Ahmad Hassan Butt; Nouman Rasool; Yaser Daanial Khan
Journal:  Mol Biol Rep       Date:  2018-09-20       Impact factor: 2.316

Review 4.  Structural Variability in the RLR-MAVS Pathway and Sensitive Detection of Viral RNAs.

Authors:  Qiu-Xing Jiang
Journal:  Med Chem       Date:  2019       Impact factor: 2.745

5.  pDHS-ELM: computational predictor for plant DNase I hypersensitive sites based on extreme learning machines.

Authors:  Shanxin Zhang; Minjun Chang; Zhiping Zhou; Xiaofeng Dai; Zhenghong Xu
Journal:  Mol Genet Genomics       Date:  2018-03-29       Impact factor: 3.291

6.  Deep4mC: systematic assessment and computational prediction for DNA N4-methylcytosine sites by deep learning.

Authors:  Haodong Xu; Peilin Jia; Zhongming Zhao
Journal:  Brief Bioinform       Date:  2021-05-20       Impact factor: 11.622

7.  Identifying N 6-methyladenosine sites in the Arabidopsis thaliana transcriptome.

Authors:  Wei Chen; Pengmian Feng; Hui Ding; Hao Lin
Journal:  Mol Genet Genomics       Date:  2016-09-02       Impact factor: 3.291

8.  i6mA-Fuse: improved and robust prediction of DNA 6 mA sites in the Rosaceae genome by fusing multiple feature representation.

Authors:  Md Mehedi Hasan; Balachandran Manavalan; Watshara Shoombuatong; Mst Shamima Khatun; Hiroyuki Kurata
Journal:  Plant Mol Biol       Date:  2020-03-05       Impact factor: 4.076

9.  RMDisease: a database of genetic variants that affect RNA modifications, with implications for epitranscriptome pathogenesis.

Authors:  Kunqi Chen; Bowen Song; Yujiao Tang; Zhen Wei; Qingru Xu; Jionglong Su; João Pedro de Magalhães; Daniel J Rigden; Jia Meng
Journal:  Nucleic Acids Res       Date:  2021-01-08       Impact factor: 16.971

10.  SAResNet: self-attention residual network for predicting DNA-protein binding.

Authors:  Long-Chen Shen; Yan Liu; Jiangning Song; Dong-Jun Yu
Journal:  Brief Bioinform       Date:  2021-09-02       Impact factor: 11.622

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