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In computing, JavaScript is a high-level, dynamic, untyped, and interpreted programming language. [Source: Wikipedia ]

miRTex

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

MicroRNAs (miRNAs) regulate a wide range of cellular and developmental processes through gene expression suppression or mRNA degradation. Experimentally validated miRNA gene targets are often reported in the literature. In this paper, we describe miRTex, a text mining system that extracts miRNA-target relations, as well as miRNA-gene and gene-miRNA regulation relations. The system achieves good precision and recall when evaluated on a literature corpus of 150 abstracts with F-scores close to 0.90 on the three different types of relations.

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miRegulome

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

miRNAs regulate post transcriptional gene expression by targeting multiple mRNAs and hence can modulate multiple signalling pathways, biological processes, and patho-physiologies. Therefore, understanding of miRNA regulatory networks is essential in order to modulate the functions of a miRNA. The focus of several existing databases is to provide information on specific aspects of miRNA regulation. However, an integrated resource on the miRNA regulome is currently not available to facilitate the exploration and understanding of miRNA regulomics.

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dPORE

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

MicroRNAs (miRNAs) are short non-coding RNA molecules that act as post-transcriptional regulators and affect the regulation of protein-coding genes. Mostly transcribed by PolII, miRNA genes are regulated at the transcriptional level similarly to protein-coding genes. In this study we focus on human miRNAs. These miRNAs are involved in a variety of pathways and can affect many diseases.

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miRspring

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

High-throughput sequencing for microRNA (miRNA) profiling has revealed a vast complexity of miRNA processing variants, but these are difficult to discern for those without bioinformatics expertise and large computing capability. In this article, we present miRNA Sequence Profiling (miRspring) (http://mirspring.victorchang.edu.au), a software solution that creates a small portable research document that visualizes, calculates and reports on the complexities of miRNA processing.

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BioVLAB-MMIA-NGS

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

It is now well established that microRNAs (miRNAs) play a critical role in regulating gene expression in a sequence-specific manner, and genome-wide efforts are underway to predict known and novel miRNA targets. However, the integrated miRNA-mRNA analysis remains a major computational challenge, requiring powerful informatics systems and bioinformatics expertise.

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tasiRNAdb

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

In plants, many trans-acting small interfering RNA (ta-siRNA) regulatory pathways have been identified as significant components of the gene networks involved in development, metabolism, responses to biotic and abiotic stresses and DNA methylation at the TAS locus.

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targetHub

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

With the expansion of high-throughput technologies, understanding different kinds of genome-level data is a common task. MicroRNA (miRNA) is increasingly profiled using high-throughput technologies (microarrays or next-generation sequencing). The downstream analysis of miRNA targets can be difficult. Although there are many databases and algorithms to predict miRNA targets, there are few tools to integrate miRNA-gene interaction data into high-throughput genomic analyses.

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APADB

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

Alternative polyadenylation (APA) is a widespread mechanism that contributes to the sophisticated dynamics of gene regulation. Approximately 50% of all protein-coding human genes harbor multiple polyadenylation (PA) sites; their selective and combinatorial use gives rise to transcript variants with differing length of their 3' untranslated region (3'UTR). Shortened variants escape UTR-mediated regulation by microRNAs (miRNAs), especially in cancer, where global 3'UTR shortening accelerates disease progression, dedifferentiation and proliferation.

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MultiMiTar

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

Machine learning based miRNA-target prediction algorithms often fail to obtain a balanced prediction accuracy in terms of both sensitivity and specificity due to lack of the gold standard of negative examples, miRNA-targeting site context specific relevant features and efficient feature selection process. Moreover, all the sequence, structure and machine learning based algorithms are unable to distribute the true positive predictions preferentially at the top of the ranked list; hence the algorithms become unreliable to the biologists.

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MIRPIPE

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

MicroRNAs (miRNAs) represent an important class of small non-coding RNAs regulating gene expression in eukaryotes. Present algorithms typically rely on genomic data to identify miRNAs and require extensive installation procedures. Niche model organisms lacking genomic sequences cannot be analyzed by such tools. Here we introduce the MIRPIPE application enabling rapid and simple browser-based miRNA homology detection and quantification.

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