New experimentally demonstrated miRecords content enhances the powerful target prioritization capabilities of IPA’s microRNA Target Filter.
REDWOOD CITY, Calif., Sept. 20, 2011 – Ingenuity® Systems, a leading provider of information and analytics solutions for life science researchers, today announced the addition of new experimentally validated microRNA-mRNA target interactions from miRecords, plus thousands of additional miRNA-mRNA interactions manually curated from additional peer-reviewed literature. The newly added content supplements existing experimentally demonstrated and predicted miRNA targets in IPA, and will be used by IPA’s microRNA Target Filter to help researchers quickly and reliably prioritize miRNA target interactions.
“IPA and its microRNA Target Filter have been very impactful for our research,” stated Arupa Ganguly, Ph.D. Professor of Genetics at the Hospital of the University of Pennsylvania. “We compared gene expression signatures of matched normal retinal tissue and retinoblastoma tumor tissue, and then used IPA for biological analysis of the data. Using microRNA and mRNA from same tumors, we [click to continue…]
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ST. LOUIS, Mo., May 5, 2011 /PRNewswire/ — Sigma Life Science, the innovative biological products and services research business of Sigma-Aldrich® (Nasdaq: SIAL), and King’s College London, today announced an exclusive license to develop and commercialize new technology for the identification and validation of microRNA (miRNA) targets in research and clinical diagnostics. For more detailed information, visit www.wherebiobegins.com/targetid.
miRNAs function as critical regulators of gene expression in eukaryotic cells, with more than 1,000 different miRNAs in the human genome already known to play multiple roles in gene regulation. Although the specific targets of most miRNAs are largely unknown, aberrant expression of miRNAs has been implicated in numerous disease states, making them important targets for clinical research in oncology, wound healing and infectious disease.
Currently, identification of miRNA targets is laborious and inefficient, relying on computer algorithms and subsequent validation by in vitro assays. To overcome this research bottleneck, scientists in the Division of Cancer Studies at King’s have developed a technology allowing simple, accurate identification and validation of miRNA targets. Dr. Joop Gaken, lead researcher of this project, explained, “The role of miRNAs in cancer is well established, and several miRNAs clearly [click to continue…]
A critical step in elucidating miRNA function is identifying potential miRNA targets and, although many computational tools have been developed for predicting animal miRNA targets, few tools are available for identifying plant miRNA targets.
There are currently three tools [miRU (Zhang, 2005), Helper tools (Moxon, et al., 2008), and TAPIR (Bonnet, et al., 2010)]
Because previous studies have demonstrated that most plant miRNAs cleave targets by perfectly or near-perfectly binding to their target, these 3 currently available tools predict plant miRNA targets based on very strictly limited criteria.
However, recent studies show that some miRNAs may inhibit translation by non-perfectly binding to target mRNAs with more potential target sites requiring a new computational program with more flexible criteria.
Target-align is available at: http://www.leonxie.com/targetAlign.php.
Xie F, Zhang B. (2010) Target-align: a tool for plant microRNA target identification. Bioinformatics [Epub ahead of print]. [abstract]
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miRecords is resource for animal miRNA-target interactions developed at the University of Minnesota. miRecords consists of two components. The Validated Targets component is a large, high-quality database of experimentally validated miRNA targets resulting from meticulous literature curation. The Predicted Targets component of miRecords is an integration of predicted miRNA targets produced by 11 established miRNA target prediction programs
PicTar is an algorithm for the identification of microRNA targets. This searchable website provides details (3′ UTR alignments with predicted sites, links to various public databases etc) regarding microRNA target predictions in vertebrates, several Drosophila species, and C. elegans.
miRanda is an algorithm for finding genomic targets for microRNAs. This algorithm has been written in C and is available as an open-source method under the GPL. MiRanda was developed at the Computational Biology Center of Memorial Sloan-Kettering Cancer Center. This software will be further developed under the open source model, coordinated by Anton Enright and Chris Sander (miranda@cbio.mskcc.org).
TargetScan: Prediction of microRNA targets – These are the most recent TargetScanS predictions (April 2005). They are essentially the 3′UTR targets reported in the Lewis et al., 2005 paper, with a few changes arising from updated gene boundary definitions from the April 2005 UCSC genome browser mapping of RefSeq mRNAs to the hg17 human genome assembly. To avoid difficulties in browser display, the few predictions spanning splice junctions are excluded. [click to continue…]
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Thanks go to our reader Qinghua Jiang who pointed out a data base called miR2Disease. This collaboration project between the Harbin Institute of Technology (HIT) and the Center of Computational Biology and Bioinformatics at the Indiana University of Medical School is a manually curated microRNA-disease database focusing on miRNA deregulation in various human diseases.
The current version (latest update Sep09) of miR2Disease documents 2663 curated relationships between 347 human microRNAs and 127 human diseases. In the initial release in Jan09 around one-seventh of the microRNA–disease relationships represented the pathogenic roles of deregulated microRNA in human disease. Each entry in the miR2Disease contains detailed information on a microRNA–disease relationship, including a microRNA ID, the disease name, a brief description of the microRNA–disease relationship, an expression pattern of the microRNA, the detection method for microRNA expression, experimentally verified target gene(s) of the microRNA and a literature reference. miR2Disease allows to search by microRNA ID, disease name, or target gene. In addition, miR2Disease offers a submission page that allows researchers to submit established microRNA–disease relationships that are not documented. Once approved by the submission review committee, the submitted records will be included in the database.
The miR2Disease database is available at: http://www.miR2Disease.org/
- Jiang Q., Wang Y., Hao Y., Juan L., Teng M., Zhang X., Li M., Wang G., Liu Y., (2009) miR2Disease: a manually curated database for microRNA deregulation in human disease. Nucleic Acids Res 37:D98-104.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2686559/
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