miRToolsGallery is a database of miRNA tools. It provides the following services: (a) Search，(b) Filter and (c) Rank the tools. 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. And it’s also very convenient for writing a tools review paper. Now we have collect above 1000 tools. miRToolsGallery will update when every new 100 tools add in. The first public online was in 1st Oct, 2016, and latest update time is 22nd April, 2018(v1.2).
A useful step for understanding the function of microRNAs (miRNA) or siRNAs is the detection of their effects on genome-wide expression profiles. Typically, approaches look for enrichment of words in the 3(')UTR sequences of the most deregulated genes. A number of tools are available for this purpose, but they require either in-depth computational knowledge, filtered 3(')UTR sequences for the genome of interest, or a set of genes acquired through an arbitrary expression cutoff.
Current challenges in microRNA (miRNA) research are to improve the identification of in vivo mRNA targets and clarify the complex interplay existing between a specific miRNA and multiple biological networks. MiRonTop is an online java web tool that integrates DNA microarrays or high-throughput sequencing data to identify the potential implication of miRNAs on a specific biological system. It allows a rapid characterization of the most pertinent mRNA targets according to several existing miRNA target prediction approaches.
A large effort to discover microRNAs (miRNAs) has been under way. Currently miRBase is their primary repository, providing annotations of primary sequences, precursors and probable genomic loci. In many cases miRNAs are identical or very similar between related (or in some cases more distant) species. However, miRBase focuses on those species for which miRNAs have been directly confirmed. Secondly, specific miRNAs or their loci are sometimes not annotated even in well-covered species.
DNA triplexes can naturally occur, co-localize and interact with many other regulatory DNA elements (e.g. G-quadruplex (G4) DNA motifs), specific DNA-binding proteins (e.g. transcription factors (TFs)), and micro-RNA (miRNA) precursors. Specific genome localizations of triplex target DNA sites (TTSs) may cause abnormalities in a double-helix DNA structure and can be directly involved in some human diseases. However, genome localization of specific TTSs, their interconnection with regulatory DNA elements and physiological roles in a cell are poor defined.
MicroRNAs (miRNAs) are small RNAs ~22 nt in length that are involved in the regulation of a variety of physiological and pathological processes. Advances in high-throughput small RNA sequencing (smRNA-seq), one of the next-generation sequencing applications, have reshaped the miRNA research landscape.
We present a new microRNA target prediction algorithm called TargetBoost, and show that the algorithm is stable and identifies more true targets than do existing algorithms. TargetBoost uses machine learning on a set of validated microRNA targets in lower organisms to create weighted sequence motifs that capture the binding characteristics between microRNAs and their targets.
