starBase v2.0 update available
starBase is a database that can be used for decoding miRNA-mRNA, miRNA-ceRNA, miRNA-lncRNA, miRNA-circRNA, miRNA-pseudogene and protein-RNA interaction networks from CLIP-Seq (HITS-CLIP, PAR-CLIP, iCLIP, CLASH) data. starBase v2.0 now also provides visualization, analysis, discovery and downloading of above-mentioned large-scale functional genomics data.
Currently, starBase v.20 includes (1)108 CLIP-Seq datasets, (2)~500,000 miRNA-mRNA interactions, (3)~10,000 miRNA-lncRNA interactions(4)~16,000 miRNA-pseudogene interactions, (5)~9,000 miRNA-circRNA interactions, (6)~10,000 ceRNA pairs, (7)~300,000 protein-RNA interactions, (8) two tools for functional annotation from ceRNA and miRNA regulatory networks.
microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) and 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 miRNAs and lncRNAs 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, we constructed TF->miRNA->mRNAs regulatory networks by integrating CLIP-Seq data and ChIP-Seq data. In addition, we constructed expression profiles of human lncRNAs and mRNAs from RNA-Seq data from 22 normal tissues.
The ChIPBase is available at http://deepbase.sysu.edu.cn/chipbase/.
Yang JH, Li JH, Jiang S, Zhou H and Qu LH.
ChIPBase: A database for decoding the transcriptional regulation of long non-coding RNA and microRNA genes from ChIP-Seq data.
Nucleic Acids Res. 2013, First published online: November 17, 2012.
Article link: http://nar.oxfordjournals.org/content/early/2012/11/16/nar.gks1060.full
The miREC database (miRNAs involved in Endometrial Cancer) combines published data about miRNAs and genes deregulated in endometrial cancer, as well as target-regulator relationships between these genes and miRNAs. All information has been extracted from published literature and entries are supplemented by reference citations.
The miREC database was launched in February 2011 by researchers at the Systems Biology Research Centre, University of Skövde, Sweden. Latest update was in March 201. Currently, miREC contains 570 genes and 154 miRNAs. These comprise genes and miRNAs found through manual curation of published literature, as well as their verified regulators and targets from miRecords and TarBase.
With two miRNA conferences coming up that focus on this field I thought the following manually curated database will be useful: miRandola.
Extracellular miRNAs in serum, plasma, saliva, urine and other body fluids have recently been shown to be associated with various pathological conditions including cancer. miRNAs circulate in the bloodstream in a highly stable, extracellular form, thus they may be used as blood-based biomarkers for cancer and other diseases. Circulating miRNAs are protected by encapsulation in membrane-bound vesicles such as exosomes, but the majority of circulating miRNAs in human plasma and serum cofractionate with Argonaute2 (Ago2) protein, rather than with vesicles. In the present work, the Ferro lab at the University of Catania performed a comprehensive classification of different extracellular circulating miRNA types. A direct link to the knowledge base miRò together with the inclusion of datamining facilities allow users to infer possible biological functions of the circulating miRNAs and their connection with the phenotype. To our knowledge miRandola is the first database that provides information about all kind of extracellular miRNAs and we believe that it will constitute a very important resource for researchers.
Single nucleotide polymorphisms (SNPs) can lead to the susceptibility and onset of diseases through their effects on gene expression at the posttranscriptional level. Recent findings indicate that SNPs could create, destroy, or modify the efficiency of miRNA binding to the 3′UTR of a gene, resulting in gene dysregulation. With the rapidly growing number of published disease-associated SNPs (dSNPs), there is a strong need for resources specifically recording dSNPs on the 3′UTRs and their nucleotide distance from miRNA target sites. Bruno et al. from the Center for Computational Research SUNY at the University of Buffalo presents miRdSNP, a database incorporating three important areas of dSNPs, miRNA target sites, and diseases.
miRdSNP provides a unique database of dSNPs on the 3′UTRs of human genes manually curated from PubMed. The current release includes 786 dSNP-disease associations for 630 unique dSNPs and 204 disease types. miRdSNP annotates genes with experimentally confirmed targeting by miRNAs and indexes miRNA target sites predicted by TargetScan and PicTar as well as potential miRNA target sites newly generated by dSNPs. A robust web interface and search tools are provided for [click to continue…]
Incoming search terms for this article: