Database Commons

a catalog of biological databases

e.g., animal; RNA; Methylation; China

Database information

ChIPBase

General information

Description: ChIPBase, an integrated resource and platform for decoding transcription factor binding maps, expression profiles and transcriptional regulation of long non-coding RNAs (lncRNAs, lincRNAs), microRNAs, other ncRNAs(snoRNAs, tRNAs, snRNAs, etc.) and protein-coding genes from ChIP-Seq data.
Year founded: 2012
Last update: 2016-11-23
Version: v2.3.4
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Country/Region: China
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Contact information

University/Institution: Sun Yat-sen University
Address: Guangzhou 510275, P.R. China
City: Guangzhou
Province/State: Guangdong
Country/Region: China
Contact name (PI/Team): Liang-Hu Qu
Contact email (PI/Helpdesk): lssqlh@mail.sysu.edu.cn

Record metadata

Created on: 2015-06-20
Curated by:
Lina Ma [2018-05-28]
Lina Ma [2017-06-21]
Lina Ma [2017-06-16]
Shixiang Sun [2017-02-13]
Shixiang Sun [2017-02-08]
Mengwei Li [2016-03-31]
Mengwei Li [2015-12-02]
Lina Ma [2015-11-27]
Mengwei Li [2015-06-27]

Ranking

All databases:
233/4549 (94.9%)
Interaction:
33/671 (95.231%)
233
Total Rank
217
Citations
31
z-index

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Publications

27924033
ChIPBase v2.0: decoding transcriptional regulatory networks of non-coding RNAs and protein-coding genes from ChIP-seq data. [PMID: 27924033]
Zhou KR, Liu S, Sun WJ, Zheng LL, Zhou H, Yang JH, Qu LH.

The abnormal transcriptional regulation of non-coding RNAs (ncRNAs) and protein-coding genes (PCGs) is contributed to various biological processes and linked with human diseases, but the underlying mechanisms remain elusive. In this study, we developed ChIPBase v2.0 (http://rna.sysu.edu.cn/chipbase/) to explore the transcriptional regulatory networks of ncRNAs and PCGs. ChIPBase v2.0 has been expanded with ?10 200 curated ChIP-seq datasets, which represent about 20 times expansion when comparing to the previous released version. We identified thousands of binding motif matrices and their binding sites from ChIP-seq data of DNA-binding proteins and predicted millions of transcriptional regulatory relationships between transcription factors (TFs) and genes. We constructed 'Regulator' module to predict hundreds of TFs and histone modifications that were involved in or affected transcription of ncRNAs and PCGs. Moreover, we built a web-based tool, Co-Expression, to explore the co-expression patterns between DNA-binding proteins and various types of genes by integrating the gene expression profiles of ?10 000 tumor samples and ?9100 normal tissues and cell lines. ChIPBase also provides a ChIP-Function tool and a genome browser to predict functions of diverse genes and visualize various ChIP-seq data. This study will greatly expand our understanding of the transcriptional regulations of ncRNAs and PCGs. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Nucleic Acids Res. 2017:45(D1) | 42 Citations (from Europe PMC, 2020-03-28)
23161675
ChIPBase: a database for decoding the transcriptional regulation of long non-coding RNA and microRNA genes from ChIP-Seq data. [PMID: 23161675]
Yang JH, Li JH, Jiang S, Zhou H, Qu LH.

Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) represent two classes of important non-coding RNAs in eukaryotes. Although these non-coding RNAs have been implicated in organismal development and in various human diseases, surprisingly little is known about their transcriptional regulation. Recent advances in chromatin immunoprecipitation with next-generation DNA sequencing (ChIP-Seq) have provided methods of detecting transcription factor binding sites (TFBSs) with unprecedented sensitivity. In this study, we describe ChIPBase (http://deepbase.sysu.edu.cn/chipbase/), a novel database that we have developed to facilitate the comprehensive annotation and discovery of transcription factor binding maps and transcriptional regulatory relationships of lncRNAs and miRNAs from ChIP-Seq data. The current release of ChIPBase includes high-throughput sequencing data that were generated by 543 ChIP-Seq experiments in diverse tissues and cell lines from six organisms. By analysing millions of TFBSs, we identified tens of thousands of TF-lncRNA and TF-miRNA regulatory relationships. Furthermore, two web-based servers were developed to annotate and discover transcriptional regulatory relationships of lncRNAs and miRNAs from ChIP-Seq data. In addition, we developed two genome browsers, deepView and genomeView, to provide integrated views of multidimensional data. Moreover, our web implementation supports diverse query types and the exploration of TFs, lncRNAs, miRNAs, gene ontologies and pathways.

Nucleic Acids Res. 2013:41(Database issue) | 175 Citations (from Europe PMC, 2020-03-28)