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.
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.
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 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.
MicroRNAs (miRNAs) are small ~22 nucleotide non-coding RNAs that function as post-transcriptional regulators of messenger RNA (mRNA) through base-pairing to 6-8 nucleotide long target sites, usually located within the mRNA 3' untranslated region. A common approach to validate and probe microRNA-mRNA interactions is to mutate predicted target sites within the mRNA and determine whether it affects miRNA-mediated activity.
MicroRNAs (miRNAs) are key gene expression regulators in plants and animals. Therefore, miRNAs are involved in several biological processes, making the study of these molecules one of the most relevant topics of molecular biology nowadays. However, characterizing miRNAs in vivo is still a complex task. As a consequence, in silico methods have been developed to predict miRNA loci. A common ab initio strategy to find miRNAs in genomic data is to search for sequences that can fold into the typical hairpin structure of miRNA precursors (pre-miRNAs).
We present POSTAR (http://POSTAR.ncrnalab.org), a resource of POST-trAnscriptional Regulation coordinated by RNA-binding proteins (RBPs). Precise characterization of post-transcriptional regulatory maps has accelerated dramatically in the past few years. Based on new studies and resources, POSTAR supplies the largest collection of experimentally probed (~23 million) and computationally predicted (approximately 117 million) RBP binding sites in the human and mouse transcriptomes.
High-throughput cell-based phenotypic screening has become an increasingly important technology for discovering new drug targets and assigning gene functions. Such experiments use hundreds of 96-well or 384-well plates, to cover whole-genome RNAi collections and/or chemical compound files, and often collect measurements that are sensitive to spatial background noise whose patterns can vary across individual plates. Correcting these position effects can substantially improve measurement accuracy and screening success.
High-throughput screening (HTS) is an indispensable tool for drug (target) discovery that currently lacks user-friendly software tools for the robust identification of putative hits from HTS experiments and for the interpretation of these findings in the context of systems biology. We developed HiTSeekR as a one-stop solution for chemical compound screens, siRNA knock-down and CRISPR/Cas9 knock-out screens, as well as microRNA inhibitor and -mimics screens.
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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