Predicts the impact of a SNP on putative microRNA targets. MicroSNiPer interrogates the 3'-untranslated region and predicts if a SNP within the target site will disrupt/eliminate or enhance/create a microRNA binding site. This application computes these sites and examines the effects of SNPs in real time. MicroSNiPer is a user-friendly Web-based tool. Its advantages include ease of use, flexibility, and straightforward graphical representation of the results.
A web-based tool for the analysis of 3' modifications of microRNAs including the loss or gain of nucleotides relative to the canonical sequence. miTRATA employs parallel processing modules to enhance its scalability when analyzing multiple small RNA (sRNA) sequencing datasets. It utilizes miRBase, currently version 21, as a source of known microRNAs for analysis. miTRATA notifies user(s) via email to download as well as visualize the results online. miTRATA's strengths lies in 1) its biologist-focused web interface, 2) improved scalability via parallel processing, and 3) its uniqueness as a webtool to perform microRNA truncation and tailing analysis.
An open-source software package for predicting microRNA target site variants (miR-TSVs) from clinical genomic data sets that measure miRNA expression, gene expression, and genotype. The main benefits of SubmiRine are that it allows for de novo prediction of miR-TSVs from custom data sets - such as those that can be generated from large-scale clinical genomics projects - and provides a methodology to prioritize predicted miR-TSVs by their relative probability of being functional. Thus, SubmiRine enables researchers to perform miR-TSV prediction efficiently and systematically on genome-scale data sets and narrow down the list of candidates to a manageable set for further validation.
Calculates features of metastable conformations determined by putative miRNA binding sites. MSbind is a Perl package that sorts meta-stable structures by number of base pairings within the target site. It approximates the opening energies of meta-stable target sites using RNAeval. It also averages the opening energy and depth of meta-stable structures.
An effective and efficient computational pipeline for detecting and visualizing editing sites and SNPs in miRNAs. The unique idea is the three-round alignment strategy with a strict control of false positive predictions. MiRME is different from the existing approaches at several aspects. First, MiRME has three progressive rounds of sequence alignment steps to reach a high sensitivity without loosing speed. Second, reads mapped to multiple loci in the genome are normalized using the cross-mapping correction method to reduce the number of false positive predictions. Third, MiRME can identify and visualize all types of editing and mutation sites at one system. Compared with six existing studies or methods, MiRME has shown much superior performance for the identification and visualization of the mutation and editing (M/E) sites of miRNAs from the ever-increasing sRNA high-throughput sequencing profiles.