1 - 50 of 71 results

ncRNAdb / Noncoding RNAs database

Gathers information about sequences and functions of transcripts which performs regulatory roles in the cell without protein-coding capacity. ncRNAdb contains about 30 000 sequences from 99 organisms. The database includes both documented RNAs and expressed sequences of Non-Coding RNAs (ncRNAs) with unknown role in cells from several class of transcripts or taxonomic groups. Searches can be made by organism name, RNA symbol or GenBank accession number and a BLAST server to perform sequence similarity searches is provided.

siRNA off-target discovery pipeline

Predicts siRNA off-target interactions and enables off-targeting potential comparisons between different siRNA designs. siRNA off-target discovery pipeline can predict the off-target transcripts and compute the off-targeting potential of a given siRNA in human. This pipeline can easily be tuned for any other organism by simply replacing the input data. This tool is able to calculate siRNA off-targeting potentials on an entire human genome/transcriptome in the time scale of hours thanks to the large-scale prediction capabilities of RIsearch.


Facilitates lincRNA discovery and characterizes aspects of lincRNA evolution. Evolinc is a two-module pipeline. The first module (Evolinc-I) is a lincRNA identification workflow that also facilitates downstream differential expression analysis and genome browser visualization of identified lincRNAs. The second module (Evolinc-II) is a genomic and transcriptomic comparative analyses workflow that determines the phylogenetic depth to which a lincRNA locus is conserved within a user-defined group of related species.

NAPP / Nucleic Acids Phylogenetic Profiling

A clustering method that efficiently identifies noncoding RNA (ncRNA) elements in a bacterial genome. This web server enables users to retrieve RNA-rich clusters from any genome in a list of 1000+ sequenced bacterial genomes. RNA-rich clusters can be viewed separately or, alternatively, all tiles from RNA-rich clusters can be contiged into larger elements and retrieved at once as a CSV or GFF file for use in a genome browser or comparison with other predictions/RNA-seq experiments.

Lncident / LncRNAs identification

Identifies Long Non-Coding RNA Identification. Lncident presents an outstanding performance on microorganism, which offers a great application prospect to the analysis of microorganism. It provides an option for the users to train a classifier on users’ own datasets, which greatly facilitates the researches who are interesting on some poor-explored species. The tool outperforms Coding-Potential Calculator, Coding-Potential Assessment Tool, Coding-Noncoding Index, and PLEK.


Allows to detect multi-disease associated co-functional microRNA pairs. PreDisRNA focuses on the detection and prioritization of multi-disease associated co-functional miRNA pairs. This tool presents a method which is based on two ideas: (1) the first is the construction of a set of reliable negative samples of disease-miRNA association through miRNA expression comparison between control and diseased subjects, (2) and the second is the use of precomputed kernel matrix for support vector machines (SVM).

SAILS / SVM-based AGO-affinity Inference for Libraries of Small RNAs

Provides a method to determine Argonaute AGO-sRNA affinity from the sRNA sequences alone. SAILS is based on a supervised machine learning approach that allows users to detect biologically functional sRNAs and their more fitted AGO protein for transcriptional silencing (TS) and post-transcriptional silencing (PTS). The algorithm can be useful to explore specific sRNA from exogenous sources or providing an alternative to AGO-IP experiments.

nRC / non-coding RNA Classifier

Classifies non-coding RNA sequences. nRC is based on deep learning (DL) architecture. It is composed of three steps: the prediction of ncRNAs secondary structures, the extraction of frequent substructures as features and the classification of known ncRNA classes. The tool can obtain better scores when compared to other machine learning algorithms. It is able to produce high scores in terms of accuracy, sensitivity, specificity, precision, F-score and Matthews Correlation Coefficient (MCC).


A platform that gathers currently more than 160 methods for broadly defined miRNA analysis. The collected tools are classified into several general and more detailed categories in which the users can additionally filter the available methods according to their specific research needs, capabilities and preferences. Tools4miRs is also a web-based target prediction meta-server that incorporates user-designated target prediction methods into the analysis of user-provided data. Tools4miRs is useful not only for bioinformaticians but also for experimental scientists in basic or applied miRNA research.

RandA / ncRNA Read-and-Analyze

Performs comprehensive ncRNA profiling and differential expression analysis on deep sequencing generated data. RandA reveals the complexity of the ncRNA repertoire in a given cell population. It maps the reads against the newly formed database using a Burrows–Wheeler transform based alignment tool summing the number of reads that mapped uniquely to each of the annotated ncRNA sequence. The tool produces a table comprising of all the mapped ncRNAs in a given sample.


Allows downloading, organization, and integrative analysis of RNA data in the Genomic Data Commons (GDC). GDCRNATools permits users to perform comprehensive analysis or integrate their own pipelines, into the workflow. The software enables users to conduct advanced analyses of RNA-seq and miRNA-seq data in GDC data portals for identification of long non-coding RNAs (lncRNA)-miRNA-mRNA competing triplets in cancer. Users can perform many analyses, including differential gene expression analysis, competing endogenous RNAs (ceRNAs) regulatory network analysis, univariate survival analysis, and functional enrichment analysis.

Bayesian Relevance Networks

Uses Bayesian reasoning about expression levels to account for the differing levels of uncertainty in expression measurements between highly- and lowly-expressed entities, and between samples with different sequencing depths. Bayesian Relevance Networks is proposed as an update to the classical and widely-used Relevance Networks algorithm with the aim of making it better suited to high-throughput sequencing data. It provides improved reproducibility in co-expression estimates and lower false discovery rates (FDR) in the resulting co-expression networks.


Allows to compile miRNA data for given target genes from public databases. MIRNA-DISTILLER implements TargetScan, microCosm, and miRDB, which may be queried independently, pairwise, or together to calculate the respective intersections. Data are stored locally for application of further analysis tools including freely definable biological parameter filters, customized output-lists for both miRNAs and target genes, and various graphical facilities. The software, a data example file and a tutorial are freely available for download.

PMM / Parallel Mixed Model

Contains R functions for fitting the Parallel Mixed Model (PMM) and analyzing its results. The PMM approach is suitable for hit selection and cross-comparison of RNAi screens generated in experiments that are performed in parallel under several conditions. PMM simultaneously takes into account all the knock-down effects in order to gain statistical power for the hit detection. As a special feature, PMM allows incorporating RNAi weights that can be assigned according to the additional information on the used RNAis or the screening quality.

siPRED / predicting siRNA

Utilizes two layers of support vector regression (SVR) to predict the efficacy of a small interfering RNA (siRNA). siPRED is based on various characteristic methods in the first layer and fusion mechanisms in the second layer. Characteristic methods were constructed by support vector regression from three categories of characteristics, namely sequence, features, and rules. In siPRED, the prediction of siRNA efficacy through integrated methods was better than through any method that utilized only a single method. siPRED is freely available on the web.


Allows users to find datasets of interest and query them using tiled-search algorithm. Geoseq aggregates and organizes libraries of short-read sequencing data. This application uses exact matches of sub-strings from a string to find inexact matches. Its user-interface provides a controlled vocabulary that assists to locate short-read libraries. The analysis service then allows mapping sequences against the short-read libraries for analysis of genes, miRNAs and other sequence types.