Similarity clustering of next-generation sequences (NGS) is an important computational problem to study the population sizes of DNA/RNA molecules and to reduce the redundancies in NGS data. Currently, most sequence clustering algorithms are limited by their speed and scalability, and thus cannot handle data with tens of millions of reads.
The Plant Small RNA Maker Site (P-SAMS) is a web tool for the simple and automated design of artificial miRNAs (amiRNAs) and synthetic trans-acting small interfering RNAs (syn-tasiRNAs) for efficient and specific targeted gene silencing in plants. P-SAMS includes two applications, P-SAMS amiRNA Designer and P-SAMS syn-tasiRNA Designer. The navigation through both applications is wizard-assisted, and the job runtime is relatively short.
MicroRNAs (miRNAs) are a class of small RNAs that post-transcriptionally regulate gene expression in animals and plants. The recent rapid advancement in miRNA biology, including high-throughput sequencing of small RNA libraries, inspired the development of a bioinformatics software, miRAuto, which predicts putative miRNAs in model plant genomes computationally. Furthermore, miRAuto enables users to identify miRNAs in non-model plant species whose genomes have yet to be fully sequenced.
MicroRNA (miRNA) sponges are RNA transcripts containing multiple high-affinity binding sites that associate with and sequester specific miRNAs to prevent them from interacting with their target messenger (m)RNAs. Due to the high specificity of miRNA sponges and strong inhibition of target miRNAs, these molecules have become increasingly applied in miRNA loss-of-function studies. However, improperly designed sponge constructs may sequester off-target miRNAs; thus, it has become increasingly important to develop a tool for miRNA sponge construct design and testing.
MicroRNAs (miRNA) are small endogenous RNA molecules, which regulate target gene expression at post-transcriptional level. Besides, miRNA activity can be controlled by a newly discovered regulatory mechanism called endogenous target mimicry (eTM). In target mimicry, eTMs bind to the corresponding miRNAs to block the binding of specific transcript leading to increase mRNA expression. Thus, miRNA-eTM-target-mRNA regulation modules involving a wide range of biological processes; an increasing need for a comprehensive eTM database arose.
Next Generation Sequencing (NGS) technology generates tens of millions of short reads for each DNA/RNA sample. A key step in NGS data analysis is the short read alignment of the generated sequences to a reference genome. Although storing alignment information in the Sequence Alignment/Map (SAM) or Binary SAM (BAM) format is now standard, biomedical researchers still have difficulty accessing this information.
DNA sequencing is used ubiquitously: from deciphering genomes to determining the primary sequence of small RNAs (smRNAs). The cloning of smRNAs is currently the most conventional method to determine the actual sequence of these important regulators of gene expression. Typical smRNA cloning projects involve the sequencing of hundreds to thousands of smRNA clones that are delimited at their 5' and 3' ends by fixed sequence regions. These primers result from the biochemical protocol used to isolate and convert the smRNA into clonable PCR products.
MicroRNAs (miRNAs) impact various biological processes within animals and plants. They complementarily bind target mRNAs, effecting a post-transcriptional negative regulation on mRNA level. The investigation of miRNA target interactions (MTIs) by high throughput screenings is challenging, as frequently used in silico target prediction tools are prone to emit false positives. This issue is aggravated for niche model organisms, where validated miRNAs and MTIs both have to be transferred from well described model organisms.
MicroRNAs (miRNAs) are a class of short, non-coding RNA that play regulatory roles in a wide variety of biological processes, such as plant growth and abiotic stress responses. Although several computational tools have been developed to identify primary miRNAs and precursor miRNAs (pre-miRNAs), very few provide the functionality of locating mature miRNAs within plant pre-miRNAs.
Competition for microRNA (miRNA) binding between RNA molecules has emerged as a novel mechanism for the regulation of eukaryotic gene expression. Competing endogenous RNA (ceRNA) can act as decoys for miRNA binding, thereby forming a ceRNA network by regulating the abundance of other RNA transcripts which share the same or similar microRNA response elements. Although this type of RNA cross talk was first described in Arabidopsis, and was subsequently shown to be active in animal models, there is no database collecting potential ceRNA data for plants.
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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