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miRTarCLIP

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

MicroRNAs (miRNAs) play a critical role in down-regulating gene expression. By coupling with Argonaute family proteins, miRNAs bind to target sites on mRNAs and employ translational repression. A large amount of miRNA-target interactions (MTIs) have been identified by the crosslinking and immunoprecipitation (CLIP) and the photoactivatable-ribonucleoside-enhanced CLIP (PAR-CLIP) along with the next-generation sequencing (NGS). PAR-CLIP shows high efficiency of RNA co-immunoprecipitation, but it also lead to T to C conversion in miRNA-RNA-protein crosslinking regions.

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IsomiRage

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

As more small RNA sequencing libraries are becoming available, it clearly emerges that microRNAs (miRNAs) are highly heterogeneous both in length and sequence. In comparison to canonical miRNAs, miRNA isoforms (termed as "isomiRs") might exhibit different biological properties, such as a different target repertoire, or enhanced/reduced stability. Nonetheless, this layer of information has remained largely unexplored due to the scarcity of small RNA NGS-datasets and the absence of proper analytical tools.

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CoMeTa

Submitted by ChenLiang on Tue, 01/09/2018 - 17:42

MicroRNAs (miRNAs) and transcription factors control eukaryotic cell proliferation, differentiation, and metabolism through their specific gene regulatory networks. However, differently from transcription factors, our understanding of the processes regulated by miRNAs is currently limited. Here, we introduce gene network analysis as a new means for gaining insight into miRNA biology.

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deepBlockAlign

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

High-throughput sequencing methods allow whole transcriptomes to be sequenced fast and cost-effectively. Short RNA sequencing provides not only quantitative expression data but also an opportunity to identify novel coding and non-coding RNAs. Many long transcripts undergo post-transcriptional processing that generates short RNA sequence fragments. Mapped back to a reference genome, they form distinctive patterns that convey information on both the structure of the parent transcript and the modalities of its processing.

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miROrtho

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

MicroRNAs (miRNAs) are short, non-protein coding RNAs that direct the widespread phenomenon of post-transcriptional regulation of metazoan genes. The mature approximately 22-nt long RNA molecules are processed from genome-encoded stem-loop structured precursor genes. Hundreds of such genes have been experimentally validated in vertebrate genomes, yet their discovery remains challenging, and substantially higher numbers have been estimated.

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miRBase Tracker

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

Since 2002, information on individual microRNAs (miRNAs), such as reference names and sequences, has been stored in miRBase, the reference database for miRNA annotation. As a result of progressive insights into the miRNome and its complexity, miRBase underwent addition and deletion of miRNA records, changes in annotated miRNA sequences and adoption of more complex naming schemes over time.

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CancerMiner

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

Little is known about the extent to which individual microRNAs (miRNAs) regulate common processes of tumor biology across diverse cancer types. Using molecular profiles of >3,000 tumors from 11 human cancer types in The Cancer Genome Atlas, we systematically analyzed expression of miRNAs and mRNAs across cancer types to infer recurrent cancer-associated miRNA-target relationships. As we expected, the inferred relationships were consistent with sequence-based predictions and published data from miRNA perturbation experiments.

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miren

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

Increasing studies have shown that the interactions between microRNAs (miRNAs) and environmental factors (EFs) play critical roles in determining phenotypes and diseases. In this study, we revealed a number of important biological insights by analyzing and modeling of miRNA-EF interactions and their relationships with human diseases. We demonstrated that the miRNA signatures of EFs could provide new information on EFs.

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workflow of integrating mRNA and miRNA expression data

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

One of the main goals in cancer studies including high-throughput microRNA (miRNA) and mRNA data is to find and assess prognostic signatures capable of predicting clinical outcome. Both mRNA and miRNA expression changes in cancer diseases are described to reflect clinical characteristics like staging and prognosis. Furthermore, miRNA abundance can directly affect target transcripts and translation in tumor cells. Prediction models are trained to identify either mRNA or miRNA signatures for patient stratification.

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miRSystem

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

Many prediction tools for microRNA (miRNA) targets have been developed, but inconsistent predictions were observed across multiple algorithms, which can make further analysis difficult. Moreover, the nomenclature of human miRNAs changes rapidly. To address these issues, we developed a web-based system, miRSystem, for converting queried miRNAs to the latest annotation and predicting the function of miRNA by integrating miRNA target gene prediction and function/pathway analyses.

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