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HuntMi

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

Machine learning techniques are known to be a powerful way of distinguishing microRNA hairpins from pseudo hairpins and have been applied in a number of recognised miRNA search tools. However, many current methods based on machine learning suffer from some drawbacks, including not addressing the class imbalance problem properly. It may lead to overlearning the majority class and/or incorrect assessment of classification performance. Moreover, those tools are effective for a narrow range of species, usually the model ones.

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RNAcentral

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

During the last decade there has been a great increase in the number of noncoding RNA genes identified, including new classes such as microRNAs and piRNAs. There is also a large growth in the amount of experimental characterization of these RNA components. Despite this growth in information, it is still difficult for researchers to access RNA data, because key data resources for noncoding RNAs have not yet been created.

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CoGemiR

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

MicroRNAs are small highly conserved non-coding RNAs which play an important role in regulating gene expression by binding the 3'UTR of target mRNAs. The majority of microRNAs are localized within other transcriptional units (host genes) and are co-expressed with them, which strongly suggests that microRNAs and corresponding host genes use the same promoter and other expression control elements. The remaining fraction of microRNAs is intergenic and is endowed with an independent regulatory region.

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ISRNA

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

Integrative Short Reads NAvigator (ISRNA) is an online toolkit for analyzing high-throughput small RNA sequencing data. Besides the high-speed genome mapping function, ISRNA provides statistics for genomic location, length distribution and nucleotide composition bias analysis of sequence reads. Number of reads mapped to known microRNAs and other classes of short non-coding RNAs, coverage of short reads on genes, expression abundance of sequence reads as well as some other analysis functions are also supported.

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SylArray

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

A useful step for understanding the function of microRNAs (miRNA) or siRNAs is the detection of their effects on genome-wide expression profiles. Typically, approaches look for enrichment of words in the 3(')UTR sequences of the most deregulated genes. A number of tools are available for this purpose, but they require either in-depth computational knowledge, filtered 3(')UTR sequences for the genome of interest, or a set of genes acquired through an arbitrary expression cutoff.

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MiRmat

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

MicroRNAs are known to be generated from primary transcripts mainly through the sequential cleavages by two enzymes, Drosha and Dicer. The sequence of a mature microRNA, especially the 'seeding sequence', largely determines its binding ability and specificity to target mRNAs. Therefore, methods that predict mature microRNA sequences with high accuracy will benefit the identification and characterization of novel microRNAs and their targets, and contribute to inferring the post-transcriptional regulation network at a genome scale.

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PAREsnip

Submitted by ChenLiang on Sun, 09/10/2017 - 16:28

Small RNAs (sRNAs) are a class of short (20-25nt) non-coding RNAs that play important regulatory roles in gene expression. An essential first step in understanding their function is to confidently identify sRNA targets. In plants, several classes of sRNAs such as microRNAs (miRNAs) and trans-acting small interfering RNAs have been shown to bind with near-perfect complementarity to their messenger RNA (mRNA) targets, generally leading to cleavage of the mRNA.

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miREvo

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

MicroRNAs (miRNAs) are small (~19-24nt) non-coding RNAs that play important roles in various biological processes. To date, the next-generation sequencing (NGS) technology has been widely used to discover miRNAs in plants and animals. Although evolutionary analysis is important to reveal the functional dynamics of miRNAs, few computational tools have been developed to analyze the evolution of miRNA sequence and expression across species, especially the newly emerged ones,

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miRMaid

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

MicroRNAs (miRNAs) are endogenous small RNAs that play a key role in post-transcriptional regulation of gene expression in animals and plants. The number of known miRNAs has increased rapidly over the years. The current release (version 14.0) of miRBase, the central online repository for miRNA annotation, comprises over 10.000 miRNA precursors from 115 different species. Furthermore, a large number of decentralized online resources are now available, each contributing with important miRNA annotation and information.

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Xenbase

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

Xenbase (http://www.xenbase.org), the Xenopus frog model organism database, integrates a wide variety of data from this biomedical model genus. Two closely related species are represented: the allotetraploid Xenopus laevis that is widely used for microinjection and tissue explant-based protocols, and the diploid Xenopus tropicalis which is used for genetics and gene targeting. The two species are extremely similar and protocols, reagents and results from each species are often interchangeable.

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