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SARS

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

The recognition of microRNA (miRNA)-binding residues in proteins is helpful to understand how miRNAs silence their target genes. It is difficult to use existing computational method to predict miRNA-binding residues in proteins due to the lack of training examples. To address this issue, unlabeled data may be exploited to help construct a computational model. Semisupervised learning deals with methods for exploiting unlabeled data in addition to labeled data automatically to improve learning performance, where no human intervention is assumed.

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AmphiEST

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

Amphioxus has been an important model for understanding the evolution of chordates and origin of vertebrates. Comparative transcriptome analysis can facilitate delineation of gene expression patterns of amphioxus at different developmental stages. So far, however, few such analyses have been performed. Here we have systematically compared amphioxus ESTs from five developmental stages. For the egg, gastrula, neurula, larva and adult stages, amphioxus ESTs were assembled, respectively, into 3364, 3230, 10,299, 4052 and 3866 contigs, and 193, 183, 933, 178 and 151 singlets.

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MDTE DB

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

MicroRNAs are crucial regulators of gene expression at post-transcriptional level. Understanding origin and evolution of miRNAs and their functions. Transposable elements (TEs) provide a natural mechanism for the origin of new miRNAs derived from TEs (MDTEs) were collected to contruct a database named MDTE database (MDTE DB) for storing, searching and analyzing MDTEs. The database proveds a convenient source for studying the origin and evolution of miRNAs.[1]

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DMPred

Submitted by ChenLiang on Tue, 01/09/2018 - 16:55

Identification of disease-associated miRNAs (disease miRNAs) is critical for understanding disease etiology and pathogenesis. Since miRNAs exert their functions by regulating the expression of their target mRNAs, several methods based on the target genes were proposed to predict disease miRNA candidates. They achieved only limited success as they all suffered from the high false-positive rate of target prediction results.

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DisSetSim

Submitted by ChenLiang on Tue, 01/09/2018 - 17:47

Functional similarity between molecules results in similar phenotypes, such as diseases. Therefore, it is an effective way to reveal the function of molecules based on their induced diseases. However, the lack of a tool for obtaining the similarity score of pair-wise disease sets (SSDS) limits this type of application.

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TarHunter

Submitted by ChenLiang on Tue, 01/09/2018 - 19:06

In plants, the targets of deeply conserved microRNAs (miRNAs) were comprehensively studied. Evidence is emerging that targets of less conserved miRNAs, endogenous target mimics (eTM) and non-canonical targets play functional roles. Existing plant miRNA prediction tools lack a cross-species conservation filter and eTM prediction function. We developed a tool named TarHunter that features a strict cross-species conservation filter and capability of predicting eTMs.

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ARTS

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

A fast growing number of non-coding RNAs have recently been discovered to play essential roles in many cellular processes. Similar to proteins, understanding the functions of these active RNAs requires methods for analyzing their tertiary structures. However, in contrast to the wide range of structure-based approaches available for proteins, there is still a lack of methods for studying RNA structures.

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iBeetle-Base

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

The iBeetle-Base (http://ibeetle-base.uni-goettingen.de) makes available annotations of RNAi phenotypes, which were gathered in a large scale RNAi screen in the red flour beetle Tribolium castaneum (iBeetle screen). In addition, it provides access to sequence information and links for all Tribolium castaneum genes.

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miRNA_Targets

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

MicroRNAs (miRNAs) are small non-coding RNAs that play a role in post-transcriptional regulation of gene expression in most eukaryotes. They help in fine-tuning gene expression by targeting messenger RNAs (mRNA). The interactions of miRNAs and mRNAs are sequence specific and computational tools have been developed to predict miRNA target sites on mRNAs, but miRNA research has been mainly focused on target sites within 3' untranslated regions (UTRs) of genes.

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MetaMirClust

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

Recent emerging studies suggest that a substantial fraction of microRNA (miRNA) genes is likely to form clusters in terms of evolutionary conservation and biological implications, posing a significant challenge for the research community and shifting the bottleneck of scientific discovery from miRNA singletons to miRNA clusters. In addition, the advance in molecular sequencing technique such as next-generation sequencing (NGS) has facilitated researchers to comprehensively characterize miRNAs with low abundance on genome-wide scale in multiple species.

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