As two kinds of important gene expression regulators, both epigenetic modification and microRNA (miRNA) can play significant roles in a wide range of human diseases. Recently, many studies have demonstrated that epigenetics and miRNA can affect each other in various ways.
Small non-coding RNAs have been significantly recognized as the key modulators in many biological processes, and are emerging as promising biomarkers for several diseases. These RNA species are transcribed in cells and can be packaged in extracellular vesicles, which are small vesicles released from many biotypes, and are involved in intercellular communication.
MicroRNAs (miRNAs) play critical roles in gene regulation. Although it is well known that multiple miRNAs may work as miRNA modules to synergistically regulate common target mRNAs, the understanding of miRNA modules is still in its infancy.
MicroRNAs play important roles in most biological processes, including cell proliferation, tissue differentiation, and embryonic development, among others. They originate from precursor transcripts (pre-miRNAs), which contain phylogenetically conserved stem-loop structures. An important bioinformatics problem is to distinguish the pre-miRNAs from pseudo pre-miRNAs that have similar stem-loop structures. We present here a novel method for tackling this bioinformatics problem.
MicroRNAs (miRNAs) regulate various biological functions by binding hundreds of transcripts to impart post-transcriptional repression. Recently, by applying a transcriptome-wide experimental method for identifying miRNA target sites (Ago HITS-CLIP), a novel non-canonical target site, named 'nucleation bulge', was discovered as widespread, functional and evolutionally conserved. Although such non-canonical nucleation bulges have been proven to be predictive by using 'pivot pairing rule' and sequence conservation, this approach has not been applied yet.
Deciphering gene regulatory networks requires the systematic identification of functional cis-acting regulatory elements. We present a suite of web-based bioinformatics tools, called GeneACT http://promoter.colorado.edu, that can rapidly detect evolutionarily conserved transcription factor binding sites or microRNA target sites that are either unique or over-represented in differentially expressed genes from DNA microarray data.
RNAomics, analogous to proteomics, concerns aspects of the secondary and tertiary structure, folding pathway, kinetics, comparison, function and regulation of all RNA in a living organism. Given recently discovered roles played by micro RNA, small interfering RNA, riboswitches, ribozymes, etc., it is important to gain insight into the folding process of RNA sequences. We describe the web server RNALOSS, which provides information about the distribution of locally optimal secondary structures, that possibly form kinetic traps in the folding process.
Transcriptional and post-transcriptional regulation of gene expression is of fundamental importance to numerous biological processes. Nowadays, an increasing amount of gene regulatory relationships have been documented in various databases and literature. However, to more efficiently exploit such knowledge for biomedical research and applications, it is necessary to construct a genome-wide regulatory network database to integrate the information on gene regulatory relationships that are widely scattered in many different places.
Being involved in many important biological processes, miRNAs can regulate gene expression by targeting mRNAs to facilitate their degradation or translational inhibition. Many miRNA sequencing studies reveal that miRNA variations such as isomiRs and "arm switching" are biologically relevant. However, existing standalone tools usually do not provide comprehensive, detailed information on miRNA variations. To deepen our understanding of miRNA variability, we developed a new standalone tool called "mirPRo" to quantify known miRNAs and predict novel miRNAs.
It is well established that the correct identification of the messenger RNA targeted by a given microRNA (miRNA) is a difficult problem, and that available methods all suffer from low specificity. We hypothesize that the correct identification of the pairing should take into account the effect of the Argonaute protein (AGO), an essential catalyst of the recognition process.
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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