Since 2002, information on individual microRNAs (miRNAs), such as reference names and sequences, has been stored in miRBase, the reference database for miRNA annotation. As a result of progressive insights into the miRNome and its complexity, miRBase underwent addition and deletion of miRNA records, changes in annotated miRNA sequences and adoption of more complex naming schemes over time.
One critical step in RNA interference (RNAi) experiments is to design small interfering RNAs (siRNAs) that can greatly reduce the expression of the target transcripts, but not of other unintended targets. Although various statistical and computational approaches have been attempted, this remains a challenge facing RNAi researchers. Here, we present a new experimentally validated method for siRNA design.
Emerging evidence has revealed phased siRNAs (phasiRNAs) as important endogenous regulators in plants. However, the integrated prediction tools for phasiRNAs are still limited. In this article, we introduce a stand-alone package PhaseTank for systematically characterizing phasiRNAs and their regulatory networks. (i) It can identify phasiRNAs/tasiRNAs functional cascades (miRNA/phasiRNA -> PHAS loci -> phasiRNA -> target) with high sensitivity and specificity.
MicroRNAs (miRNAs) are small non-coding single-stranded RNAs (20-23 nts) that are known to act as post-transcriptional and translational regulators of gene expression. Although, they were initially overlooked, their role in many important biological processes, such as development, cell differentiation, and cancer has been established in recent times. In spite of their biological significance, the identification of miRNA genes in newly sequenced organisms is still based, to a large degree, on extensive use of evolutionary conservation, which is not always available.
The diversity of microRNAs and small-interfering RNAs has been extensively explored within angiosperms by focusing on a few key organisms such as Oryza sativa and Arabidopsis thaliana. A deeper division of the plants is defined by the radiation of the angiosperms and gymnosperms, with the latter comprising the commercially important conifers. The conifers are expected to provide important information regarding the evolution of highly conserved small regulatory RNAs.
miRDeepFinder is a software package developed to identify and functionally analyze plant microRNAs (miRNAs) and their targets from small RNA datasets obtained from deep sequencing. The functions available in miRDeepFinder include pre-processing of raw data, identifying conserved miRNAs, mining and classifying novel miRNAs, miRNA expression profiling, predicting miRNA targets, and gene pathway and gene network analysis involving miRNAs.
MicroRNAs (miRNAs) are a recently discovered class of non-coding RNAs that regulate gene and protein expression in plants and animals. MiRNAs have so far been identified mostly by specific cloning of small RNA molecules, complemented by computational methods. We present a computational identification approach that is able to identify candidate miRNA homologs in any set of sequences, given a query miRNA. The approach is based on a sequence similarity search step followed by a set of structural filters.[1]
Off-target effects are one of the most serious problems in RNA interference (RNAi). Here, we present dsCheck (http://dsCheck.RNAi.jp/), web-based online software for estimating off-target effects caused by the long double-stranded RNA (dsRNA) used in RNAi studies. In the biochemical process of RNAi, the long dsRNA is cleaved by Dicer into short-interfering RNA (siRNA) cocktails. The software simulates this process and investigates individual 19 nt substrings of the long dsRNA.
miRNAs are small non coding RNA structures which play important roles in biological processes. Finding miRNA precursors in genomes is therefore an important task, where computational methods are required. The goal of these methods is to select potential pre-miRNAs which could be validated by experimental methods. With the new generation of sequencing techniques, it is important to have fast algorithms that are able to treat whole genomes in acceptable times.
Artificially synthesized short interfering RNAs (siRNAs) are widely used in functional genomics to knock down specific target genes. One ongoing challenge is to guarantee that the siRNA does not elicit off-target effects. Initial reports suggested that siRNAs were highly sequence-specific; however, subsequent data indicates that this is not necessarily the case.
Our database aim to make it easy for researchers to find the right tools or data source for their own specific study in miRNA field. Now we have collect >1000 tools. This database will update when every new 100 tools add in. Last update time 22nd April, 2018 (v1.2).
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