MicroRNAs are small, non-coding RNA molecules that can complementarily bind to the mRNA 3'-UTR region to regulate the gene expression by transcriptional repression or induction of mRNA degradation. Increasing evidence suggests a new mechanism by which miRNAs may regulate target gene expression by binding in promoter and amino acid coding regions. Most of the existing databases on miRNAs are restricted to mRNA 3'-UTR region.
The noncoding RNAs and protein related biomacromolecules interaction database (NPInter; http://bioinfo.ibp.ac.cn/NPInter or http://www.bioinfo.org.cn/NPInter) is a database that documents experimentally determined functional interactions between noncoding RNAs (ncRNAs) and protein related biomacromolecules (PRMs) (proteins, mRNAs or genomic DNAs).
Polymorphism in microRNA Target Site (PolymiRTS) database is a collection of naturally occurring DNA variations in putative microRNA target sites. PolymiRTSs may affect gene expression and cause variations in complex phenotypes. The database integrates sequence polymorphism, phenotype and expression microarray data, and characterizes PolymiRTSs as potential candidates responsible for the quantitative trait locus (QTL) effects. It is a resource for studying PolymiRTSs and their implications in phenotypic variations.
Numerous regulatory structural motifs have been identified as playing essential roles in transcriptional and post-transcriptional regulation of gene expression. RegRNA is an integrated web server for identifying the homologs of regulatory RNA motifs and elements against an input mRNA sequence. Both sequence homologs and structural homologs of regulatory RNA motifs can be recognized.
We demonstrate that paired expression profiles of microRNAs (miRNAs) and mRNAs can be used to identify functional miRNA-target relationships with high precision. We used a Bayesian data analysis algorithm, GenMiR++, to identify a network of 1,597 high-confidence target predictions for 104 human miRNAs, which was supported by RNA expression data across 88 tissues and cell types, sequence complementarity and comparative genomics data.
Here, we present LNCipedia (http://www.lncipedia.org), a novel database for human long non-coding RNA (lncRNA) transcripts and genes. LncRNAs constitute a large and diverse class of non-coding RNA genes. Although several lncRNAs have been functionally annotated, the majority remains to be characterized.
During the last few years, several new small regulatory RNAs (sRNAs) have been discovered in bacteria. Most of them act as post-transcriptional regulators by base pairing to a target mRNA, causing translational repression or activation, or mRNA degradation. Numerous sRNAs have already been identified, but the number of experimentally verified targets is considerably lower. Consequently, computational target prediction is in great demand.
High-throughput gene expression experiments are widely used to identify the role of genes involved in biological conditions of interest. MicroRNAs (miRNA) are regulatory molecules that have been functionally associated with several developmental programs and their deregulation with diverse diseases including cancer.
The CluePedia Cytoscape plugin is a search tool for new markers potentially associated to pathways. CluePedia calculates linear and non-linear statistical dependencies from experimental data. Genes, proteins and miRNAs can be connected based on in silico and/or experimental information and integrated into a ClueGO network of terms/pathways. Interrelations within each pathway can be investigated, and new potential associations may be revealed through gene/protein/miRNA enrichments. A pathway-like visualization can be created using the Cerebral plugin layout.
The interaction between genetic factors and environmental factors has critical roles in determining the phenotype of an organism. In recent years, a number of studies have reported that the dysfunctions on microRNA (miRNAs), environmental factors and their interactions have strong effects on phenotypes and even may result in abnormal phenotypes and diseases, whereas there has been no a database linking miRNAs, environmental factors and phenotypes.
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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