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miRU
An automated plant miRNA target prediction server.
The server aims at predicting plant miRNA targets with the highest sensitivity and selectivity by using a search algorithm which guarantees finding all homologous sequences within given mismatches, and by applying current knowledge about miRNA targets to minimize false positives. As a practical tool, it should aid biologists in plant miRNA research.
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MicroInspector
A web tool for detection of miRNA binding sites in an RNA sequence.
Here, we describe the web tool MicroInspector that will analyse a user-defined RNA sequence, which is typically an mRNA or a part of an mRNA, for the occurrence of binding sites for known and registered miRNAs. The program allows variation of temperature, the setting of energy values as well as the selection of different miRNA databases to identify miRNA-binding sites of different strength. MicroInspector could spot the correct sites for miRNA-interaction in known target mRNAs. Using other mRNAs, for which such an interaction has not yet been described, we discovered frequently potential miRNA binding sites of similar quality, which can now be analysed experimentally. The MicroInspector program is easy to use and does not require specific computer skills. The service can be accessed via the MicroInspector web server at http://www.imbb.forth.gr/microinspector.
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miRNAMap
Genomic maps of microRNA genes and their target genes in mammalian genomes.
This work develops an integrated database, miRNAMap, to store the known miRNA genes, the putative miRNA genes, the known miRNA targets and the putative miRNA targets. The known miRNA genes in four mammalian genomes such as human, mouse, rat and dog are obtained from miRBase, and experimentally validated miRNA targets are identified in a survey of the literature. Putative miRNA precursors were identified by RNAz, which is a non-coding RNA prediction tool based on comparative sequence analysis. The mature miRNA of the putative miRNA genes is accurately determined using a machine learning approach, mmiRNA. Then, miRanda was applied to predict the miRNA targets within the conserved regions in 3'-UTR of the genes in the four mammalian genomes. The miRNAMap also provides the expression profiles of the known miRNAs, cross-species comparisons, gene annotations and cross-links to other biological databases. Both textual and graphical web interface are provided to facilitate the retrieval of data from the miRNAMap. The database is freely available at http://mirnamap.mbc.nctu.edu.tw/.
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miRBase
MicroRNA sequences, targets and gene nomenclature.
The miRBase database aims to provide integrated interfaces to comprehensive microRNA sequence data, annotation and predicted gene targets. miRBase takes over functionality from the microRNA Registry and fulfils three main roles: the miRBase Registry acts as an independent arbiter of microRNA gene nomenclature, assigning names prior to publication of novel miRNA sequences. miRBase Sequences is the primary online repository for miRNA sequence data and annotation. miRBase Targets is a comprehensive new database of predicted miRNA target genes. miRBase is available at http://microrna.sanger.ac.uk/.
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miRanda
Finds potential target sites for miRNAs in genomic sequence.
MicroRNAs (miRNAs) interact with target mRNAs at specific sites to induce cleavage of the message or inhibit translation. The specific function of most mammalian miRNAs is unknown. We have predicted target sites on the 3' untranslated regions of human gene transcripts for all currently known 218 mammalian miRNAs to facilitate focused experiments. We report about 2,000 human genes with miRNA target sites conserved in mammals and about 250 human genes conserved as targets between mammals and fish. The prediction algorithm optimizes sequence complementarity using position-specific rules and relies on strict requirements of interspecies conservation. Experimental support for the validity of the method comes from known targets and from strong enrichment of predicted targets in mRNAs associated with the fragile X mental retardation protein in mammals. This is consistent with the hypothesis that miRNAs act as sequence-specific adaptors in the interaction of ribonuclear particles with translationally regulated messages. Overrepresented groups of targets include mRNAs coding for transcription factors, components of the miRNA machinery, and other proteins involved in translational regulation, as well as components of the ubiquitin machinery, representing novel feedback loops in gene regulation. Detailed information about target genes, target processes, and open-source software for target prediction (miRanda) is available at http://www.microrna.org. Our analysis suggests that miRNA genes, which are about 1% of all human genes, regulate protein production for 10% or more of all human genes. |
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RNAhybrid
Fast and effective prediction of microRNA/target duplexes.
MicroRNAs (miRNAs) are short RNAs that post-transcriptionally regulate the expression of target genes by binding to the target
mRNAs. Although a large number of animal miRNAs has been defined, only a few targets are known. In contrast to plant
miRNAs, which usually bind nearly perfectly to their targets, animal miRNAs bind less tightly, with a few nucleotides being
unbound, thus producing more complex secondary structures of miRNA/target duplexes. Here, we present a program, RNAhybrid,
that predicts multiple potential binding sites of miRNAs in large target RNAs. In general, the program finds the
energetically most favorable hybridization sites of a small RNA in a large RNA. Intramolecular hybridizations, that is, base
pairings between target nucleotides or between miRNA nucleotides are not allowed. For large targets, the time complexity of
the algorithm is linear in the target length, allowing many long targets to be searched in a short time. Statistical significance of
predicted targets is assessed with an extreme value statistics of length normalized minimum free energies, a Poisson approximation
of multiple binding sites, and the calculation of effective numbers of orthologous targets in comparative studies of
multiple organisms. We applied our method to the prediction of Drosophila miRNA targets in 3'-UTRs and coding sequence.
RNAhybrid, with its accompanying programs RNAcalibrate and RNAeffective, is available for download and as a Web tool on
the Bielefeld Bioinformatics Server (http://bibiserv.techfak.uni-bielefeld.de/rnahybrid/). |
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TargetScanS
Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets.
We predict regulatory targets of vertebrate microRNAs (miRNAs) by identifying mRNAs with conserved complementarity to the seed (nucleotides 2–7) of the miRNA. An overrepresentation of conserved adenosines flanking the seed complementary sites in mRNAs indicates that primary sequence determinants can supplement base pairing to specify miRNA target recognition. In a four-genome analysis of 3′ UTRs, approximately 13,000 regulatory relationships were detected above the estimate of false-positive predictions, thereby implicating as miRNA targets more than 5300 human genes, which represented 30% of our gene set. Targeting was also detected in open reading frames. In sum, well over one third of human genes appear to be conserved miRNA targets. |
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- Griffiths-Jones, S., Grocock, R.J., van Dongen, S., Bateman, A. and Enright, A.J. (2006) miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res, 34, D140-144.
- Hsu, P.W., Huang, H.D., Hsu, S.D., Lin, L.Z., Tsou, A.P., Tseng, C.P., Stadler, P.F., Washietl, S. and Hofacker, I.L. (2006) miRNAMap: genomic maps of microRNA genes and their target genes in mammalian genomes. Nucleic Acids Res, 34, D135-139.
- John, B., Enright, A.J., Aravin, A., Tuschl, T., Sander, C. and Marks, D.S. (2004) Human MicroRNA targets. PLoS Biol, 2, e363.
- Rusinov, V., Baev, V., Minkov, I.N. and Tabler, M. (2005) MicroInspector: a web tool for detection of miRNA binding sites in an RNA sequence. Nucleic Acids Res, 33, W696-700.
- Zhang, Y. (2005) miRU: an automated plant miRNA target prediction server. Nucleic Acids Res, 33, W701-704.
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BidLab, Institute of Bioinformatics, National Chiao Tung University , Taiwan.
Contact us:bryan@mail.nctu.edu.tw with questions or comments
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