Tools and Databases

microRNA Target Prediction Algorithms

microCLIP

microCLIP (http://www.microrna.gr/microCLIP) algorithm can be used for the transcriptome-wide identification of miRNA-target interactions. It operates on AGO-PAR-CLIP sequencing reads, requiring a SAM/BAM alignment file and a list of miRNAs as minimum input. microCLIP framework combines deep learning classifiers under a super learning scheme for CLIP-guided detection of miRNA interactions. The model incorporates a series of significant breakthroughs in PAR-CLIP analysis, revolutionizing the experiment’s scope and robustness

Target Prediction

DIANA-microT-CDS

DIANA-microT-CDS (http://www.microrna.gr/microT-CDS) is the 5th version of the microT algorithm. It is specifically trained on a positive and a negative set of miRNA Recognition Elements (MREs) located in both the 3′-UTR and CDS regions. DIANA-microT-CDS delivers a significant increase in sensitivity relative to the previous version (65% vs. 52%), evaluated using experimental proteomics data. It exhibited the highest sensitivity at any level of specificity, when compared against other state-of-the-art implementations.

Databases of experimentally supported microRNA (non-)coding targets

TarBase v8.0

TarBase v8.0 (http://www.microrna.gr/tarbase) is a reference database devoted to the indexing of experimentally supported microRNA (miRNA) targets. DIANA-TarBase is coming of age, with more than a decade of continuous support in the non-coding RNA field. It comprises ~1 million entries, the largest compilation of miRNA–gene interactions compared to any relevant database.

Experimentally Supported

LncBase v2.0

LncBase v2.0 (http://www.microrna.gr/Lncbase) presents an extensive collection of miRNA:lncRNA interactions. More than 70,000 low and high-throughput, (in)direct miRNA:lncRNA experimentally supported interactions, derived from manually curated publications and the analysis of 153 AGO CLIP-Seq libraries are indexed. LncBase v2 also hosts in silico predicted miRNA targets on lncRNAs, identified with the DIANA-microT algorithm.

Characterization of microRNA Promoters and their Regulators

microTSS

How to detect the elusive microRNA genes

microTSS (http://www.microrna.gr/microTSS/) microTSS is a machine-learning algorithm that provides highly accurate, single-nucleotide resolution predictions for intergenic miRNA transcription start sites (TSSs). microTSS integrates high-resolution RNA-Seq data with active transcription marks derived from chromatin immunoprecipitation and DNase-Seq to enable the characterization of tissue-specific promoters. microTSS is readily applicable to any cell or tissue samples and constitutes the missing part towards integrating the regulation of miRNA transcription into the modelling of tissue-specific regulatory networks.

Transciption Factors

miRGen v3.0

Elucidating the combinatorial effect of miRNAs on molecular pathways

miRGen v3.0 (http://www.microrna.gr/mirgen) provides accurate cell-line-specific miRNA gene Transcription Start Sites (TSSs), coupled with genome-wide maps of Transcription Factor Binding Sites (TFBSs). More than 7.3 billion RNA-, ChIP- and DNase-Seq next generation sequencing reads were analyzed/assembled and combined with state-of-the-art miRNA TSS prediction and TFBS identification algorithms.

Incorporating microRNAs in Pathways

miRPath v3.0

Elucidating the combinatorial effect of miRNAs on molecular pathways

miRPath v3.0 (http://www.microrna.gr/miRPathv3) is an online software suite dedicated to the assessment of miRNA regulatory roles and the identification of controlled pathways.

The new miRPath web server renders possible the functional annotation of one or more miRNAs using standard (hypergeometric distributions), unbiased empirical distributions and/or meta-analysis statistics. Gene Ontology and KEGG Pathway terms are currently supported in 7 species.

Pathways

Uncovering microRNAs and Transcription Factors with Crucial Roles in NGS Expression Data

mirExTra v2.0

mirExTra v2.0 (http://www.microrna.gr/mirextrav2) performs a combined Differential Expression Analysis (DEA) of mRNAs and miRNAs to uncover miRNAs and transcription factors (TFs) playing important regulatory roles between two investigated states. The web server utilizes miRNA:mRNA, TF:mRNA and TF:miRNA interactions derived from extensive experimental data sets, enabling users to uncover central regulators within sequencing data: miRNAs controlling mRNAs and TFs regulating mRNA or miRNA expression.

miExTra

Web Servers

DIANA-web server 5.0

DIANA web server v5.0 has innate support to the Ensembl (v.69), miRBase (miRBase 18) version and nomenclature, while keeping backwards compatibility with all previous miRBase versions for selected tools, such as DIANA-TarBase. All available tools have been extended to support by default Drosophila melanogaster and Caenorhabditis elegans (as well as Homo sapiens and Mus musculus). DIANA web server also supports a series of sophisticated workflows enabling users without the necessary bioinformatics infrastructure to perform advanced multi-step functional miRNA analyses. All available tools and databases are now accessible programmatically by a REST web service interface. DIANA-Web Server v5.0 provides extensive support for Biological Workflow Management Applications such as Taverna. Specifically, a DIANA-labs Plug-in has been developed, which embeds into the Taverna arsenal all the available tools and services. Furthermore, DIANA services and example workflows are available in major relevant websites such as BioCatalogue and myExperiment.