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MicroRNA target databases | Non-coding transcript data analysis

MicroRNAs (miRNAs) are a class of endogenous non-coding RNAs with ∼22 nucleotides (nt) that play important roles at the post-transcriptional level in animals and plants (Bartel, 2004). The mechanistic model of miRNAs regulates gene expression either by repressing mRNA translation or by inducing mRNA degradation by partial complementarity binding with target sequences (Engels and Hutvagner, 2006). Source text: Chou et al., 2016.

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Generates a map of predicted transcription factor binding sites (TFBS) and small RNA target sites for the whole Arabidopsis thaliana genome. AthaMap can be used for bioinformatic predictions of putative regulatory sites. Several online web tools are available that address specific questions. Starting with the identification of transcription factor-binding sites (TFBS) in any gene of interest, colocalizing TFBS can be identified as well as common TFBS in a set of user-provided genes. Furthermore, genes can be identified that are potentially targeted by specific transcription factors or small inhibitory RNAs.
A resource for animal miRNA–target interactions. miRecords consists of two components. The validated targets component is a large, high-quality database of experimentally validated miRNA targets resulting from meticulous manual literature curation. As the largest known collection of experimental validated miRNA targets, it emphasizes systematic and structured documentation of experimental support of miRNA–target interactions. This database not only serves the experimental researchers by providing the lists of confirmed targets of the miRNAs of their interest, but also provides a large and high-quality dataset that will facilitate the development of the next-generation miRNA target prediction programs. The Predicted Targets component of miRecords is an integration of predicted miRNA targets produced by 11 established miRNA target prediction programs. As the most complete integration of predicted miRNA targets, it is expected to provide considerable help to researchers investigating new miRNA targets.
Gathers over 152 million human miRNA–target predictions obtained from 30 independent resources. mirDIP provides an integrative score assigned to each unique miRNA–target interaction. This repository simplifies two tasks: (1) identifying downstream gene targets of selected miRNAs or genes of interest; and (2) providing confirmation of the miRNA–gene associations derived from prior experiments. It allows results to be summarized in a wide format in the miRNA– gene matrix tab, where miRNA–gene interactions are represented by an adjacency matrix.
Provides for the first time hundreds of thousands of high quality manually curated experimentally validated miRNA:gene interactions, enhanced with detailed meta-data. With DIANA-TarBase v7.0 you can easily identify positive or negative experimental results, the utilized experimental methodology, experimental conditions including cell/tissue type and treatment. The new interface provides also advanced information ranging from the binding site location, as identified experimentally as well as in silico, to the primer sequences used for cloning experiments.
microRNA body map
A repository of RT-qPCR miRNA expression data and functional miRNA annotation in normal and diseased human tissues. The miRNA bodymap enables prioritization of candidate miRNAs based on their expression pattern or functional annotation across tissue or disease subgroup. The miRNA bodymap web tool enables researchers to upload additional data sets of matching mRNA and miRNA expression data to populate the database with additional functional miRNA predictions. In this way, miRNA functions that are predicted in multiple independent data sets can be further prioritized, making the miRNA bodymap a community resource for functional miRNA research.
A model designed to predict miRNA target sites using more relaxed miRNA-target binding characteristics. miRTar2GO allows for the prediction of cell-type specific miRNA targets. It was trained on the common rules of miRNA-target interactions, Argonaute (Ago) CLIP-Seq data and experimentally validated miRNA target interactions. miRTar2GO provides four different prediction modes specifically designed to adjust the sensitivity. The designed adjustment levels are based on thermodynamic features of the verified interactions. These variations in sensitivity are designed to decrease the false-positive rate and increase the true-negative rate. Target predictions, binding specifications, results of the pathway analysis and gene ontology enrichment of miRNA targets are freely available online.
DPMIND / Degradome-based Plant MiRNA-Target Interaction and Network Database
Verifies the predicted relationships between miRNA and their targets via degradome data. DPMIND is a plant miRNA repository and compiles plant degradome data. This database offers to users several query interfaces and graphical visualization pages to ease the access of verified miR-Tar interactions (MTIs) and degradome-based miRNA regulatory networks (MRNs). It provides assistance to study the conservation and specificity of miR-Tar interactions and sub-networks of plant tissues or species.
Collects interactions formed by molecules of interest across diverse cancer types. CancerNet contains human cancer-specific microRNA- (miRNA) target interactions, protein-protein interactions (PPI) and functionally synergistic miRNA pairs organized under more than 30 human cancer types. It can identify poorly annotated miRNAs and protein-coding genes interacted with molecules. This repository intends to find the roles of miRNAs in tumorigenesis from a system-level perspective.
HCSGD / Human Cellular Senescence Gene Database
Assists users on human cellular senescence. HCSGD combines multiple online published data sources into a senescence gene annotation platform. Genes are annotated with gene ontology (GO) annotation and microRNA/drug/compound target information. This software provides features like visualization of cellular senescence gene networks, browsing annotated functional information and the recovering senescence-associated genes with a web interface.
A database of miRNA binding sites. STarMirDB presents predictions for all three mRNA regions and for both seed and seedless sites. Importantly, it presents a probability for each site as an indicator of confidence in the prediction. STarMirDB can be searched by miRNAs or mRNAs separately or in combination. The search results are categorized into seed and seedless sites in 3' UTR, CDS and 5' UTR. For each predicted site, STarMirDB provides a comprehensive list of sequence, thermodynamic and target structural features that are known to influence miRNA: target interaction. A high resolution PDF diagram of the conformation of the miRNA:target hybrid is also available for visualization and publication. The results of a database search are available through both an interactive viewer and downloadable text files.
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A web-based system for converting queried miRNAs to the latest annotation and predicting the function of miRNA by integrating miRNA target gene prediction and function/pathway analyses. First, queried miRNA IDs were converted to the latest annotated version to prevent potential conflicts resulting from multiple aliases. Next, by combining seven algorithms and two validated databases, potential gene targets of miRNAs and their functions were predicted based on the consistency across independent algorithms and observed/expected ratios. Lastly, five pathway databases were included to characterize the enriched pathways of target genes through bootstrap approaches. Based on the enriched pathways of target genes, the functions of queried miRNAs could be predicted.
Provides predictions that reflect the in vivo combinatorial nature of miRNAs from a large collection of differentially expressed transcripts and miRNAs. The miRror-Suite platform includes the miRror2.0 and Probability Supported Iterative miRror (PSI-miRror) tools. Researchers who performed large-scale transcriptomics or miRNA profiling experiments from cells and tissues will benefit from miRror-Suite. miRror-Suite provides a concise, plausible explanation for the regulation of miRNAs in such complex settings.
BCIP / Breast Cancer Integrative Platform
Maintains multi-omics data selected with strict quality control and processed with uniform normalization methods. BCIP is a database that provides a user-friendly interface integrating comprehensive and flexible analysis tools on differential gene expression from 9005 tumor and 376 normal tissue samples, copy number variation (CNV) from 3035 tumor samples, microRNA-target interactions, co-expressed genes, KEGG pathways, mammary tissue-specific gene functional networks and survival analysis.
MtiBase / MiRNA-target interactions database
A database that identify CDS-located and 5'UTR-located miRNA binding sites and systematically evaluate miRNA regulatory effects on mRNA stability and translation by integrating multiple high-throughput experimental datasets such as Ago CLIP-seq (HITS-CLIP, PAR-CLIP, iCLIP, CLASH), mRNA profiles, ribosome-protected fragment sequencing (RPF) and pulsed stable isotope labeling with amino acids in culture (pSILAC). MtiBase used 61 Ago CLIP-seq datasets to reduce the rates of false positive target prediction. To assess miRNA regulatory effects on mRNA stability, 222 mRNA profiles in response to miRNA overexpression, knockdown, or knockout were integrated. Moreover, 28 RPF and six pSILAC were applied to assess the effects of miRNAs on translational efficiency and protein synthesis, respectively. The SNP influence to the regulatory effects of CDS-located and 5'UTR-located miRNA binding sites was also systematically investigated.
A database of predicted and validated miRNA binding sites and correlated SNPs in human genome. dbSMR has a user-friendly interface where the information can be queried using either the gene name, microRNA name, polymorphism ID or transcript ID. Combination queries using 'AND' or 'OR' is also possible along with specifying the degree of change of intramolecular bonding with and without the polymorphism. Such a resource would enable researchers address questions like the role of regulatory SNPs in the 3' UTRs and population specific regulatory modulations in the context of microRNA targets.
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