A fast growing number of non-coding RNAs have recently been discovered to play essential roles in many cellular processes. Similar to proteins, understanding the functions of these active RNAs requires methods for analyzing their tertiary structures. However, in contrast to the wide range of structure-based approaches available for proteins, there is still a lack of methods for studying RNA structures.
: Next-Generation Sequencing (NGS) technology has revealed that microRNAs (miRNAs) are capable of exhibiting frequent differences from their corresponding mature reference sequences, generating multiple variants: the isoforms of miRNAs (isomiRs). These isomiRs mainly originate via the imprecise and alternative cleavage during the pre-miRNA processing and post-transcriptional modifications that influence miRNA stability, their sub-cellular localization and target selection.
High-throughput screening (HTS) is a common technique for both drug discovery and basic research, but researchers often struggle with how best to derive hits from HTS data. While a wide range of hit identification techniques exist, little information is available about their sensitivity and specificity, especially in comparison to each other. To address this, we have developed the open-source NoiseMaker software tool for generation of realistically noisy virtual screens.
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.
MicroRNAs are a predominant type of small non-coding RNAs approximately 21 nucleotides in length that play an essential role at the post-transcriptional level by either RNA degradation, translational repression or both through an RNA-induced silencing complex. Identification of these molecules can aid the dissecting of their regulatory functions. The secondary structures of plant pre-miRNAs are much more complex than those of animal pre-miRNAs. In contrast to prediction tools for animal pre-miRNAs, much less effort has been contributed to plant pre-miRNAs.
The computational prediction of novel microRNA within a full genome involves identifying sequences having the highest chance of being a miRNA precursor (pre-miRNA). These sequences are usually named candidates to miRNA. The well-known pre-miRNAs are usually only a few in comparison to the hundreds of thousands of potential candidates to miRNA that have to be analyzed, which makes this task a high classimbalance classification problem.
In this note, we propose an R function named NqA (Normalization qPCR Array, where qPCR is quantitative real-time polymerase chain reaction) suitable for the identification of a set of microRNAs (miRNAs) to be used for data normalization in view of subsequent validation studies with qPCR data.
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 miRBase database is the central and official repository for miRNAs and the current release is miRBase version 21.0. Name changes in different miRBase releases cause inconsistencies in miRNA names from version to version. When working with only a small number of miRNAs the translation can be done manually. However, with large sets of miRNAs, the necessary correction of such inconsistencies becomes burdensome and error-prone.
We have developed T7 RNAi Oligo Designer (TROD), a web application for RNA interference studies. TROD greatly facilitates the design of oligodeoxynucleotide sequences for the in vitro production of siRNA duplexes with T7 RNA polymerase. Given a query cDNA sequence, the program scans for appropriate target sequences based on the constraints of the T7 RNA polymerase method and published criteria for RNA interference with siRNAs.
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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