Literature DB >> 33045745

SilencerDB: a comprehensive database of silencers.

Wanwen Zeng1,2, Shengquan Chen1, Xuejian Cui1, Xiaoyang Chen1, Zijing Gao1, Rui Jiang1.   

Abstract

Gene regulatory elements, including promoters, enhancers, silencers, etc., control transcriptional programs in a spatiotemporal manner. Though these elements are known to be able to induce either positive or negative transcriptional control, the community has been mostly studying enhancers which amplify transcription initiation, with less emphasis given to silencers which repress gene expression. To facilitate the study of silencers and the investigation of their potential roles in transcriptional control, we developed SilencerDB (http://health.tsinghua.edu.cn/silencerdb/), a comprehensive database of silencers by manually curating silencers from 2300 published articles. The current version, SilencerDB 1.0, contains (1) 33 060 validated silencers from experimental methods, and (ii) 5 045 547 predicted silencers from state-of-the-art machine learning methods. The functionality of SilencerDB includes (a) standardized categorization of silencers in a tree-structured class hierarchy based on species, organ, tissue and cell line and (b) comprehensive annotations of silencers with the nearest gene and potential regulatory genes. SilencerDB, to the best of our knowledge, is the first comprehensive database at this scale dedicated to silencers, with reliable annotations and user-friendly interactive database features. We believe this database has the potential to enable advanced understanding of silencers in regulatory mechanisms and to empower researchers to devise diverse applications of silencers in disease development.
© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.

Entities:  

Year:  2021        PMID: 33045745     DOI: 10.1093/nar/gkaa839

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  6 in total

1.  OpenAnnotate: a web server to annotate the chromatin accessibility of genomic regions.

Authors:  Shengquan Chen; Qiao Liu; Xuejian Cui; Zhanying Feng; Chunquan Li; Xiaowo Wang; Xuegong Zhang; Yong Wang; Rui Jiang
Journal:  Nucleic Acids Res       Date:  2021-07-02       Impact factor: 16.971

2.  scEnhancer: a single-cell enhancer resource with annotation across hundreds of tissue/cell types in three species.

Authors:  Tianshun Gao; Zilong Zheng; Yihang Pan; Chengming Zhu; Fuxin Wei; Jinqiu Yuan; Rui Sun; Shuo Fang; Nan Wang; Yang Zhou; Jiang Qian
Journal:  Nucleic Acids Res       Date:  2022-01-07       Impact factor: 16.971

Review 3.  Transcriptional Silencers: Driving Gene Expression with the Brakes On.

Authors:  Julian A Segert; Stephen S Gisselbrecht; Martha L Bulyk
Journal:  Trends Genet       Date:  2021-03-09       Impact factor: 11.821

4.  Leveraging cell-type-specific regulatory networks to interpret genetic variants in abdominal aortic aneurysm.

Authors:  Shining Ma; Xi Chen; Xiang Zhu; Philip S Tsao; Wing Hung Wong
Journal:  Proc Natl Acad Sci U S A       Date:  2022-01-04       Impact factor: 11.205

5.  Integration of Count Difference and Curve Similarity in Negative Regulatory Element Detection.

Authors:  Na He; Wenjing Wang; Chao Fang; Yongjian Tan; Li Li; Chunhui Hou
Journal:  Front Genet       Date:  2022-02-18       Impact factor: 4.599

6.  DeepCAPE: A Deep Convolutional Neural Network for the Accurate Prediction of Enhancers.

Authors:  Shengquan Chen; Mingxin Gan; Hairong Lv; Rui Jiang
Journal:  Genomics Proteomics Bioinformatics       Date:  2021-02-11       Impact factor: 6.409

  6 in total

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