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NRDR

Submitted by ChenLiang on Thu, 10/20/2016 - 20:36

Large-scale transcriptome projects have shown that the number of RNA transcripts not coding for proteins (non-coding RNAs) is much larger than previously recognized. High-throughput technologies, coupled with bioinformatics approaches, have produced increasing amounts of data, highlighting the role of non-coding RNAs (ncRNAs) in biological processes. Data generated by these studies include diverse non-coding RNA classes from organisms of different kingdoms, which were obtained using different experimental and computational assays.

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StarScan

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

Endogenous small non-coding RNAs (sRNAs), including microRNAs, PIWI-interacting RNAs and small interfering RNAs, play important gene regulatory roles in animals and plants by pairing to the protein-coding and non-coding transcripts. However, computationally assigning these various sRNAs to their regulatory target genes remains technically challenging. Recently, a high-throughput degradome sequencing method was applied to identify biologically relevant sRNA cleavage sites.

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Screensaver

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

Shared-usage high throughput screening (HTS) facilities are becoming more common in academe as large-scale small molecule and genome-scale RNAi screening strategies are adopted for basic research purposes. These shared facilities require a unique informatics infrastructure that must not only provide access to and analysis of screening data, but must also manage the administrative and technical challenges associated with conducting numerous, interleaved screening efforts run by multiple independent research groups.

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sRNAMap

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

Small non-coding RNAs (sRNAs) carry out a variety of biological functions and affect protein synthesis and protein activities in prokaryotes. Recently, numerous sRNAs and their targets were identified in Escherichia coli and in other bacteria. It is crucial to have a comprehensive resource concerning the annotation of small non-coding RNAs in microbial genomes.

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MiRNA GO Annotation Manual

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

MicroRNA regulation of developmental and cellular processes is a relatively new field of study, and the available research data have not been organized to enable its inclusion in pathway and network analysis tools. The association of gene products with terms from the Gene Ontology is an effective method to analyze functional data, but until recently there has been no substantial effort dedicated to applying Gene Ontology terms to microRNAs.

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Geoseq

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

Datasets generated on deep-sequencing platforms have been deposited in various public repositories such as the Gene Expression Omnibus (GEO), Sequence Read Archive (SRA) hosted by the NCBI, or the DNA Data Bank of Japan (ddbj). Despite being rich data sources, they have not been used much due to the difficulty in locating and analyzing datasets of interest.

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mirSOM

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

MicroRNAs (miRNAs) are small non-coding RNAs that regulate transcriptional processes via binding to the target gene mRNA. In animals, this binding is imperfect, which makes the computational prediction of animal miRNA targets a challenging task. The accuracy of miRNA target prediction can be improved with the use of machine learning methods. Previous work has described methods using supervised learning, but they suffer from the lack of adequate training examples, a common problem in miRNA target identification, which often leads to deficient generalization ability.

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miRBoost

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

Identification of microRNAs (miRNAs) is an important step toward understanding post-transcriptional gene regulation and miRNA-related pathology. Difficulties in identifying miRNAs through experimental techniques combined with the huge amount of data from new sequencing technologies have made in silico discrimination of bona fide miRNA precursors from non-miRNA hairpin-like structures an important topic in bioinformatics. Among various techniques developed for this classification problem, machine learning approaches have proved to be the most promising.

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miRNA-deKmer

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

The microRNA (miRNA), a small non-coding RNA molecule, plays an important role in transcriptional and post-transcriptional regulation of gene expression. Its abnormal expression, however, has been observed in many cancers and other disease states, implying that the miRNA molecules are also deeply involved in these diseases, particularly in carcinogenesis. Therefore, it is important for both basic research and miRNA-based therapy to discriminate the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops).

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SolmiRNA

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

MicroRNAs (miRNAs) are a class of small, single-stranded, noncoding RNAs ranging from 19 to 25 nucleotides. The miRNA control various cellular functions by negatively regulating gene expression at the post-transcriptional level. The miRNA regulation over their target genes has a central role in regulating plant growth and development; however, only a few reports have been published on the function of miRNAs in the family Solanaceae.

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