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miRNA Binding Site

Antar

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

Microarray expression analyses following miRNA transfection/inhibition and, more recently, Argonaute cross-linked immunoprecipitation (CLIP)-seq assays have been used to detect miRNA target sites. CLIP and expression approaches measure differing stages of miRNA functioning-initial binding of the miRNP complex and subsequent message repression. We use nonparametric predictive models to characterize a large number of known target and flanking features, utilizing miRNA transfection, HITS-CLIP, and PAR-CLIP data.

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MicroMUMMIE

Submitted by ChenLiang on Sun, 09/10/2017 - 20:22

High-throughput sequencing has opened numerous possibilities for the identification of regulatory RNA-binding events. Cross-linking and immunoprecipitation of Argonaute proteins can pinpoint a microRNA (miRNA) target site within tens of bases but leaves the identity of the miRNA unresolved. A flexible computational framework, microMUMMIE, integrates sequence with cross-linking features and reliably identifies the miRNA family involved in each binding event.

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Sfold

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

The Sfold web server provides user-friendly access to Sfold, a recently developed nucleic acid folding software package, via the World Wide Web (WWW). The software is based on a new statistical sampling paradigm for the prediction of RNA secondary structure. One of the main objectives of this software is to offer computational tools for the rational design of RNA-targeting nucleic acids, which include small interfering RNAs (siRNAs), antisense oligonucleotides and trans-cleaving ribozymes for gene knock-down studies.

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5
Average: 5 (2 votes)

MBSTAR

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

MicroRNA (miRNA) regulates gene expression by binding to specific sites in the 3'untranslated regions of its target genes. Machine learning based miRNA target prediction algorithms first extract a set of features from potential binding sites (PBSs) in the mRNA and then train a classifier to distinguish targets from non-targets. However, they do not consider whether the PBSs are functional or not, and consequently result in high false positive rates. This substantially affects the follow up functional validation by experiments.

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LNCipedia

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

Here, we present LNCipedia (http://www.lncipedia.org), a novel database for human long non-coding RNA (lncRNA) transcripts and genes. LncRNAs constitute a large and diverse class of non-coding RNA genes. Although several lncRNAs have been functionally annotated, the majority remains to be characterized.

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IntaRNA

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

During the last few years, several new small regulatory RNAs (sRNAs) have been discovered in bacteria. Most of them act as post-transcriptional regulators by base pairing to a target mRNA, causing translational repression or activation, or mRNA degradation. Numerous sRNAs have already been identified, but the number of experimentally verified targets is considerably lower. Consequently, computational target prediction is in great demand.

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miRNASNP

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

MicroRNAs (miRNAs) are studied as key regulators of gene expression involved in different diseases. Several single nucleotide polymorphisms (SNPs) in miRNA genes or target sites (miRNA-related SNPs) have been proved to be associated with human diseases by affecting the miRNA-mediated regulatory function. To systematically analyze miRNA-related SNPs and their effects, we performed a genome-wide scan for SNPs in human pre-miRNAs, miRNA flanking regions, target sites, and designed a pipeline to predict the effects of them on miRNA-target interaction.

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MicroSNiPer

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

MicroRNAs are short, approximately 22 nucleotide noncoding RNAs binding to partially complementary sites in the 3'UTR of target mRNAs. This process generally results in repression of multiple targets by a particular microRNA. There is substantial interest in methods designed to predict the microRNA targets and effect of single nucleotide polymorphisms (SNPs) on microRNA binding, given the impact of microRNA on posttranscriptional regulation and its potential relation to complex diseases.

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Patrocles

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

Studying the muscular hypertrophy of Texel sheep by forward genetics, we have identified an A-to-G transition in the 3'UTR of the GDF8 gene that reveals an illegitimate target site for microRNAs miR-1 and miR-206 that are highly expressed in skeletal muscle. This causes the down-regulation of this muscle-specific chalone and hence contributes to the muscular hypertrophy of Texel sheep.

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SiteSifter

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

Recognition sites for microRNAs (miRNAs) have been reported to be located in the 3' untranslated regions of transcripts. In a computational screen for highly conserved motifs within coding regions, we found an excess of sequences conserved at the nucleotide level within coding regions in the human genome, the highest scoring of which are enriched for miRNA target sequences.

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5
Average: 5 (2 votes)

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