Recent discovery of thousands of small and large noncoding RNAs, in parallel to technical improvements enabling scientists to study the transcriptome in much higher depth, has resulted in massive data generation. This burst of information prompts the development of easily accessible resources for storage, retrieval and analysis of raw and processed data, and hundreds of Web-based tools dedicated to these tasks have been made available.
In plants, the targets of deeply conserved microRNAs (miRNAs) were comprehensively studied. Evidence is emerging that targets of less conserved miRNAs, endogenous target mimics (eTM) and non-canonical targets play functional roles. Existing plant miRNA prediction tools lack a cross-species conservation filter and eTM prediction function. We developed a tool named TarHunter that features a strict cross-species conservation filter and capability of predicting eTMs.
Small RNA sequencing is the most widely used tool for microRNA (miRNA) discovery, and shows great potential for the efficient study of miRNA cross-species transport, i.e., by detecting the presence of exogenous miRNA sequences in the host species. Because of the increased appreciation of dietary miRNAs and their far-reaching implication in human health, research interests are currently growing with regard to exogenous miRNAs bioavailability, mechanisms of cross-species transport and miRNA function in cellular biological processes.
The double helix is a conformation that genomic DNA usually assumes; under certain conditions, however, guanine-rich DNA sequences can form a four-stranded structure, G-quadruplex, which is found to play a role in regulating gene expression. Indeed, it has been demonstrated that the G-quadruplex formed in the c-MYC promoter suppresses its transcriptional activity. Recent studies suggest that G-quadruplex motifs (GQMs) are enriched in human gene promoters.
MicroRNAs, by regulating the expression of hundreds of target genes, play critical roles in developmental biology and the etiology of numerous diseases, including cancer. As a vast amount of microRNA expression profile data are now publicly available, the integration of microRNA expression data sets with gene expression profiles is a key research problem in life science research.
Growing evidence demonstrates that local well-ordered structures are closely correlated with cis-acting elements in the post-transcriptional regulation of gene expression. The prediction of a well-ordered folding sequence (WFS) in genomic sequences is very helpful in the determination of local RNA elements with structure-dependent functions in mRNAs.
MicroRNAs (miRNAs) are small non-coding RNAs that play a role in post-transcriptional regulation of gene expression in most eukaryotes. They help in fine-tuning gene expression by targeting messenger RNAs (mRNA). The interactions of miRNAs and mRNAs are sequence specific and computational tools have been developed to predict miRNA target sites on mRNAs, but miRNA research has been mainly focused on target sites within 3' untranslated regions (UTRs) of genes.
In recent times, information on miRNAs and their binding sites is gaining momentum. Therefore, there is interest in the development of tools extracting miRNA related information from known literature. Hence, we describe GeneAFinder and miRAFinder scripts (open source) developed using python programming for the semi-automatic extraction and arrangement of updated information on miRNAs, genes and additional data from published article abstracts in PubMed. The scripts are suitable for custom modification as per requirement.
This report describes the miRQuest - a novel middleware available in a Web server that allows the end user to do the miRNA research in a user-friendly way. It is known that there are many prediction tools for microRNA (miRNA) identification that use different programming languages and methods to realize this task. It is difficult to understand each tool and apply it to diverse datasets and organisms available for miRNA analysis. miRQuest can easily be used by biologists and researchers with limited experience with bioinformatics.
The computational identification of non-coding RNA regions on the genome is currently receiving much attention. However, it is essentially harder than gene-finding problems for protein-coding regions because non-coding RNA sequences do not have strong statistical signals. Since comparative sequence analysis is effective for non-coding RNA detection, efficient computational methods are expected for structural alignment of RNA sequences.
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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