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Target Prediction

TargetFinder

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

Plants and animals use small RNAs (microRNAs [miRNAs] and siRNAs) as guides for posttranscriptional and epigenetic regulation. In plants, miRNAs and trans-acting (ta) siRNAs form through distinct biogenesis pathways, although they both interact with target transcripts and guide cleavage. An integrated approach to identify targets of Arabidopsis thaliana miRNAs and ta-siRNAs revealed several new classes of small RNA-regulated genes, including conventional genes such as Argonaute2 and an E2-ubiquitin conjugating enzyme.

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ElMMo

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

MicroRNAs have emerged as important regulatory genes in a variety of cellular processes and, in recent years, hundreds of such genes have been discovered in animals. In contrast, functional annotations are available only for a very small fraction of these miRNAs, and even in these cases only partially.

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RNA22

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

We present rna22, a method for identifying microRNA binding sites and their corresponding heteroduplexes. Rna22 does not rely upon cross-species conservation, is resilient to noise, and, unlike previous methods, it first finds putative microRNA binding sites in the sequence of interest, then identifies the targeting microRNA. Computationally, we show that rna22 identifies most of the currently known heteroduplexes. Experimentally, with luciferase assays, we demonstrate average repressions of 30% or more for 168 of 226 tested targets.

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5
Average: 5 (2 votes)

miRU

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

MicroRNAs (miRNAs) play important roles in gene expression regulation in animals and plants. Since plant miRNAs recognize their target mRNAs by near-perfect base pairing, computational sequence similarity search can be used to identify potential targets. A web-based integrated computing system, miRU, has been developed for plant miRNA target gene prediction in any plant, if a large number of sequences are available.

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Average: 4.5 (2 votes)

mirWIP

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

Target prediction for animal microRNAs (miRNAs) has been hindered by the small number of verified targets available to evaluate the accuracy of predicted miRNA-target interactions. Recently, a dataset of 3,404 miRNA-associated mRNA transcripts was identified by immunoprecipitation of the RNA-induced silencing complex components AIN-1 and AIN-2.

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MPSS

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

A class of eukaryotic non-coding RNAs termed microRNAs (miRNAs) interact with target mRNAs by sequence complementarity to regulate their expression. The low abundance of some miRNAs and their time- and tissue-specific expression patterns make experimental miRNA identification difficult. We present here a computational method for genome-wide prediction of Arabidopsis thaliana microRNAs and their target mRNAs. This method uses characteristic features of known plant miRNAs as criteria to search for miRNAs conserved between Arabidopsis and Oryza sativa.

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DIANA-LncBase

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

Recently, the attention of the research community has been focused on long non-coding RNAs (lncRNAs) and their physiological/pathological implications. As the number of experiments increase in a rapid rate and transcriptional units are better annotated, databases indexing lncRNA properties and function gradually become essential tools to this process. Aim of DIANA-LncBase (www.microrna.gr/LncBase) is to reinforce researchers' attempts and unravel microRNA (miRNA)-lncRNA putative functional interactions.

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Average: 5 (1 vote)

MicroTar

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

The accurate prediction of a comprehensive set of messenger RNAs (targets) regulated by animal microRNAs (miRNAs) remains an open problem. In particular, the prediction of targets that do not possess evolutionarily conserved complementarity to their miRNA regulators is not adequately addressed by current tools.

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Arabidopsis Small RNA Project Database

Submitted by ChenLiang on Tue, 01/09/2018 - 17:35

MicroRNAs (miRNAs) are an extensive class of tiny RNA molecules that regulate the expression of target genes by means of complementary base pair interactions. Although the first miRNAs were discovered in Caenorhabditis elegans, >300 miRNAs were recently documented in animals and plants, both by cloning methods and computational predictions. We present a genome-wide computational approach to detect miRNA genes in the Arabidopsis thaliana genome.

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MIRZA

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

We introduce a biophysical model of miRNA-target interaction and infer its parameters from Argonaute 2 cross-linking and immunoprecipitation data. We show that a substantial fraction of human miRNA target sites are noncanonical and that predicted target-site affinity correlates well with the extent of target destabilization. Our model provides a rigorous biophysical approach to miRNA target identification beyond ad hoc miRNA seed-based methods.[1]

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