Non-coding RNAs (ncRNA) account for a large portion of the transcribed genomic output. This diverse family of untranslated RNA molecules play a crucial role in cellular function. The use of 'deep sequencing' technology (also known as 'next generation sequencing') to infer transcript expression levels in general, and ncRNA specifically, is becoming increasingly common in molecular and clinical laboratories.
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.
We introduce a novel web-based tool, miSEA, for evaluating the enrichment of relevant microRNA sets from microarray and miRNA-Seq experiments on paired samples, e.g. control vs.
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.
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.
In plants, post transcriptional regulation by non-coding RNAs (ncRNAs), in particular miRNAs (19-24 nt) has been involved in modulating the transcriptional landscape in developmental, biotic and abiotic interactions. In past few years, considerable focus has been leveraged on delineating and deciphering the role of miRNAs and their canonical isomiRs in plants. However, proper classification and accurate prediction of plant isomiRs taking into account the relative features by which we define isomiRs, such as templated or non-templated is still lacking.
Compared with complementary DNA (cDNA) or messenger RNA (mRNA) microarray data, microRNA (miRNA) microarray data are harder to normalize due to the facts that the total number of miRNAs is small, and that the majority of miRNAs usually have low expression levels. In bead-based microarrays, the hybridization is completed in several pools. As a result, the number of miRNAs tested in each pool is even smaller, which poses extra difficulty to intrasample normalization and ultimately affects the quality of the final profiles assembled from various pools.
Validation of clinical biomarkers and response to therapy is a challenging topic in cancer research. An important source of information for virtual validation is the datasets generated from multi-center cancer research projects such as The Cancer Genome Atlas project (TCGA). These data enable investigation of genetic and epigenetic changes responsible for cancer onset and progression, response to cancer therapies, and discovery of the molecular profiles of various cancers.
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.
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.
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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