MicroRNAs (miRNAs) are short single-stranded non-coding molecules that usually function as negative regulators to silence or suppress gene expression. Owning to the dynamic nature of miRNA and reduced microarray and sequencing costs, a growing number of researchers are now measuring high-dimensional miRNA expression data using repeated or multiple measures in which each individual has more than one sample collected and measured over time.
A specialized orchid database, named Orchidstra (URL: http://orchidstra.abrc.sinica.edu.tw), has been constructed to collect, annotate and share genomic information for orchid functional genomics studies. The Orchidaceae is a large family of Angiosperms that exhibits extraordinary biodiversity in terms of both the number of species and their distribution worldwide.
High-throughput small RNA (sRNA) sequencing technology enables an entirely new perspective for plant microRNA (miRNA) research and has immense potential to unravel regulatory networks. Novel insights gained through data mining in publically available rich resource of sRNA data will help in designing biotechnology-based approaches for crop improvement to enhance plant yield and nutritional value. Bioinformatics resources enabling meta-analysis of miRNA expression across multiple plant species are still evolving.
MicroRNAs are important genetic regulators in both animals and plants. They have a range of functions spanning development, differentiation, growth, metabolism and disease. The advent of next-generation sequencing technologies has made it a relatively straightforward task to detect these molecules and their relative expression via sequencing. There are a large number of published studies with deposited datasets. However, there are currently few resources that capitalize on these data to better understand the features, distribution and biogenesis of miRNAs.
MicroRNAs are short RNAs that serve as regulators of gene expression and are essential components of normal development as well as modulators of disease. MicroRNAs generally act cell-autonomously, and thus their localization to specific cell types is needed to guide our understanding of microRNA activity. Current tissue-level data have caused considerable confusion, and comprehensive cell-level data do not yet exist. Here, we establish the landscape of human cell-specific microRNA expression.
There is little data considering relationships among human RNA, demographic variables, and primary human cell physiology. The platelet RNA and expression-1 study measured platelet aggregation to arachidonic acid, ADP, protease-activated receptor (PAR) 1 activation peptide (PAR1-AP), and PAR4-AP, as well as mRNA and microRNA (miRNA) levels in platelets from 84 white and 70 black healthy subjects. A total of 5911 uniquely mapped mRNAs and 181 miRNAs were commonly expressed and validated in a separate cohort.
Experimentally validated co-expression correlations between miRNAs and genes are a valuable resource to corroborate observations about miRNA/mRNA changes after experimental perturbations, as well as compare miRNA target predictions with empirical observations. For example, when a given miRNA is transcribed, true targets of that miRNA should tend to have lower expression levels relative to when the miRNA is not expressed.
Pancreatic cancer is the fourth leading cause of cancer-related death in the world. The etiology of pancreatic cancer is heterogeneous with a wide range of alterations that have already been reported at the level of the genome, transcriptome, and proteome. The past decade has witnessed a large number of experimental studies using high-throughput technology platforms to identify genes whose expression at the transcript or protein levels is altered in pancreatic cancer.
The study of microRNAs (miRNAs) is attracting great considerations. Recent studies revealed that miRNAs play as important regulators of gene expression and some even as cancer players or inhibitors. Many studies try to discover new miRNAs and reveal the miRNA expression profile in cancer using a SAGE-based total RNA clone method. However, the data processing of this method is labor-intensive with several different biological databases and more than ten data processing steps involved.
microRNAs (miRNAs) are small (20-23 nt), non-coding single stranded RNA molecules that act as post-transcriptional regulators of mRNA gene expression. They have been implicated in regulation of developmental processes in diverse organisms. The echinoderms, Strongylocentrotus purpuratus (sea urchin) and Patiria miniata (sea star) are excellent model organisms for studying development with well-characterized transcriptional networks.
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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