Literature DB >> 33835461

WHISTLE: A Functionally Annotated High-Accuracy Map of Human m6A Epitranscriptome.

Qingru Xu1, Kunqi Chen2,3, Jia Meng1,4.   

Abstract

N6-Methyladenosine (m6A) is the most prevalent posttranscriptional modification in eukaryotes and plays a pivotal role in various biological processes, such as splicing, RNA degradation, and RNA-protein interaction. Accurately identification of the location of m6A is essential for related downstream studies. In this chapter, we introduce a prediction framework WHISTLE, which enables us to acquire so far the most accurate map of the transcriptome-wide human m6A RNA-methylation sites (with an average AUC: 0.948 and 0.880 under the full transcript or mature messenger RNA models, respectively, when tested on independent datasets). Besides, each individual m6A site was also functionally annotated according to the "guilt-by-association" principle by integrating RNA methylation data, gene expression data and protein-protein interaction data. A web server was constructed for conveniently querying the predicted RNA methylation sites and their putative biological functions. The website supports the query by genes, by GO function, table view, and the download of all the functionally annotated map of predicted map of human m6A epitranscriptome. The WHISTLE web server is freely available at: www.xjtlu.edu.cn/biologicalsciences/whistle and http://whistle-epitranscriptome.com .

Entities:  

Keywords:  Epitranscriptome; Guilt-by-association; Machine learning; N6-Methyladenosine (m6A); RNA modifications

Year:  2021        PMID: 33835461     DOI: 10.1007/978-1-0716-1307-8_28

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  1 in total

1.  Ten simple rules for effective online outreach.

Authors:  Holly M Bik; Alistair D M Dove; Miriam C Goldstein; Rebecca R Helm; Rick MacPherson; Kim Martini; Alexandria Warneke; Craig McClain
Journal:  PLoS Comput Biol       Date:  2015-04-16       Impact factor: 4.475

  1 in total
  5 in total

1.  Deepm5C: A deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy.

Authors:  Md Mehedi Hasan; Sho Tsukiyama; Jae Youl Cho; Hiroyuki Kurata; Md Ashad Alam; Xiaowen Liu; Balachandran Manavalan; Hong-Wen Deng
Journal:  Mol Ther       Date:  2022-05-06       Impact factor: 12.910

2.  m5CRegpred: Epitranscriptome Target Prediction of 5-Methylcytosine (m5C) Regulators Based on Sequencing Features.

Authors:  Zhizhou He; Jing Xu; Haoran Shi; Shuxiang Wu
Journal:  Genes (Basel)       Date:  2022-04-12       Impact factor: 4.141

Review 3.  Research Progress for RNA Modifications in Physiological and Pathological Angiogenesis.

Authors:  Hui-Ming Chen; Hang Li; Meng-Xian Lin; Wei-Jie Fan; Yi Zhang; Yan-Ting Lin; Shu-Xiang Wu
Journal:  Front Genet       Date:  2022-07-22       Impact factor: 4.772

4.  m5C-Related lncRNAs Predict Overall Survival of Patients and Regulate the Tumor Immune Microenvironment in Lung Adenocarcinoma.

Authors:  Junfan Pan; Zhidong Huang; Yiquan Xu
Journal:  Front Cell Dev Biol       Date:  2021-06-29

5.  CircMET promotes tumor proliferation by enhancing CDKN2A mRNA decay and upregulating SMAD3.

Authors:  Lei Yang; Yi Chen; Ning Liu; Yanwen Lu; Wenliang Ma; Zhenhao Yang; Weidong Gan; Dongmei Li
Journal:  Mol Cancer       Date:  2022-01-18       Impact factor: 27.401

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.