Tag Archives: repTar

Tip of the Week: A year in tips III (last half of 2010)

As you may know, we’ve been doing tips-of-the-week for three years now. We have completed around 150 little tidbit introductions to various resources. At the end of the year we’ve established a sort of holiday tradition: we are doing a summary post to collect them all. If you have missed any of them it’s a great way to have a quick look at what might be useful to your work.

Here are the tips from the first half of the year, and below you will find the tips from the last half of 2010 (you can see past years’ tips here: 2008 I2008 II2009 I2009 II):


July 7: Mint for Protein Interactions, an introduction to MINT to study protein-protein interactions
July 14: Introduction to Changes to NCBI’s Protein Database, as it states :D
July 21: 1000 Genome Project Browser, 1000 Genomes project has pilot data out, this is the browser.
July 28: R Genetics at Galaxy, the Galaxy analysis and workflow tool added R genetics analysis tools.


August 4: YeastMine, SGD adds an InterMine capability to their database search.
August 11: Gaggle Genome Browser, a tool to allow for the visualization of genomic data, part of the “gaggle components”
August 18: Brenda, comprehensive enzyme information.
August 25: Mouse Genomic Pathology, unlike other tips, this is not a video but rather a detailed introduction to a new website.


September 1: Galaxy Pages, and introduction to the new community documentation and sharing capability at Galaxy.
September 8: Varitas. A Plaid Database. A resource that integrates human variation data such as SNPs and CNVs.
September 15: CircuitsDB for TF/miRNA/gene regulation networks.
September 21: Pathcase for pathway data.
September 29: Comparative Toxicogenomics Database (CTD), VennViewer. A new tool to create Venn diagrams to compare associated datasets for genes, diseases or chemicals.


October 6: BioExtract Server, a server that allows researcher to store data, analyze data and create workflows of data.
October 13: NCBI Epigenomics, “Beyond the Genome” NCBI’s site for information and data on epigenetics.
October 20: Comparing Microbial Databases including IMG, UCSC Microbial and Archeal browsers, CMR and others.
October 27: iTOL, interactive tree of life


November 3: VISTA Enhancer Browser explore possible regulatory elements with comparative genomics
November 10: Getting canonical gene info from the UCSC Browser. Need one gene version to ‘rule them all’?
November 17: ENCODE Data in the UCSC Genome Browser, an entire 35 minute tutorial on the ENCODE project.
November 24: FLink. A tool that links items in one NCBI database to another in a meaningful and weighted manner.


December 1: PhylomeDB. A database of gene phylogenies of many species.
December 8: BioGPS for expression data and more.
December 15: RepTar, a database of miRNA target sites.

Tip of the Week: RepTar, a database of miRNA target sites

microRNAs have become a rich source of research as they probably have a huge effect on gene expression and disease. The human genome may encode over 1,000 miRNAs that target over half of our genes. They might be implicated in a lot of common diseases (which not yet have been picked up in GWAS studies?). They are a fascinating area of biology that has only come of it’s on in the last decade. As such, the number of databases to catalog miRNAs is large. Today’s tip is on a new one, RepTar, which is reported in the upcoming NAR database issue. The niche RepTar is attempting to fill is to get predictions of miRNAs more comprehensive by including new research in the algorithm. This new research suggests there are more possible target sites than previously thought. As mentioned in the article,

Recently, the miRNA binding options were expanded further with the identification of ‘centered sites’, functional miRNA target sites that lack both perfect seed pairing and 3′-compensatory pairing and instead exhibit pairing with the target along 11–12 contiguous pairs at the center of the miRNA (4). While some algorithms relaxed the evolutionary conservation criterion (5–11) and/or offer also predictions of 3′-compensatory sites [e.g. (6,12,13)], few databases offer predictions of the whole repertoire of miRNA targeting patterns. Furthermore to date, no database lists genome-wide prediction of cellular targets of viral miRNAs. These miRNAs lack significant evolutionary conservation and their targets are not necessarily expected to be evolutionarily conserved. In addition, the few identified viral miRNA targets have shown both conventional seed binding and 3′-compensatory binding [e.g. (3,14)].

Here we present a database of genome-wide miRNA target predictions for mouse and human genes, based on the predictions of our novel target prediction algorithm, RepTar

I’ll leave the predictive value up to miRNA researchers, but I thought I’d introduce the site.

While I’m at it, allow me to list a few other miRNA sites from labs and institutes as far flung as China, Italy, Israel, Canada and the U.S.. Perhaps someday I’ll do a comparison.

CircuitsDB, which Jennifer did a great tip of the week tutorial on.

miRBase, which we have a full-length tutorial on.
PicTar, they have an annotation track for UCSC Genome Browser
PuTmiR (in relation to transcription factors)

two lists to catch some others: http://mirnablog.com/microrna-target-prediction-tools/ and  http://www.ncrna.org/KnowledgeBase/link-database/mirna_target_database

Elefant, N., Berger, A., Shein, H., Hofree, M., Margalit, H., & Altuvia, Y. (2010). RepTar: a database of predicted cellular targets of host and viral miRNAs Nucleic Acids Research DOI: 10.1093/nar/gkq1233