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C-mii

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

MicroRNAs (miRNAs) have been known to play an important role in several biological processes in both animals and plants. Although several tools for miRNA and target identification are available, the number of tools tailored towards plants is limited, and those that are available have specific functionality, lack graphical user interfaces, and restrict the number of input sequences. Large-scale computational identifications of miRNAs and/or targets of several plants have been also reported.

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CSCdb

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

Cancer stem cells (CSCs), which have the ability to self-renew and differentiate into various tumor cell types, are a special class of tumor cells. Characterizing the genes involved in CSCs regulation is fundamental to understand the mechanisms underlying the biological process and develop treatment methods for tumor therapy. Recently, much effort has been expended in the study of CSCs and a large amount of data has been generated. However, to the best of our knowledge, database dedicated to CSCs is not available until now.

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RAmiRNA

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

MicroRNAs (miRNAs) are short endogenous non-coding RNA molecules that regulate protein coding gene expression in animals, plants, fungi, algae and viruses through the RNA interference pathway. By virtue of their base complementarity, mature miRNAs stop the process of translation, thus acting as one of the important molecules in vivo. Attempts to predict precursor-miRNAs and mature miRNAs have been achieved in a significant number of model organisms but development of prediction models aiming at relatively less studied organisms are rare.

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LMMEL-miR-miner

Submitted by ChenLiang on Mon, 01/09/2017 - 10:31

BACKGROUND: In many cancers, microRNAs (miRs) contribute to metastatic progression by modulating phenotypic reprogramming processes such as epithelial-mesenchymal plasticity. This can be driven by miRs targeting multiple mRNA transcripts, inducing regulated changes across large sets of genes. The miR-target databases TargetScan and DIANA-microT predict putative relationships by examining sequence complementarity between miRs and mRNAs.

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miSTAR

Submitted by ChenLiang on Mon, 01/09/2017 - 11:43

In microRNA (miRNA) target prediction, typically two levels of information need to be modeled: the number of potential miRNA binding sites present in a target mRNA and the genomic context of each individual site. Single model structures insufficiently cope with this complex training data structure, consisting of feature vectors of unequal length as a consequence of the varying number of miRNA binding sites in different mRNAs. To circumvent this problem, we developed a two-layered, stacked model, in which the influence of binding site context is separately modeled.

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RAIN

Submitted by ChenLiang on Thu, 04/06/2017 - 18:52

Protein association networks can be inferred from a range of resources including experimental data, literature mining and computational predictions. These types of evidence are emerging for non-coding RNAs (ncRNAs) as well. However, integration of ncRNAs into protein association networks is challenging due to data heterogeneity. Here, we present a database of ncRNA-RNA and ncRNA-protein interactions and its integration with the STRING database of protein-protein interactions.

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sRNAnalyzer

Submitted by ChenLiang on Tue, 01/09/2018 - 19:05

Although many tools have been developed to analyze small RNA sequencing (sRNA-Seq) data, it remains challenging to accurately analyze the small RNA population, mainly due to multiple sequence ID assignment caused by short read length. Additional issues in small RNA analysis include low consistency of microRNA (miRNA) measurement results across different platforms, miRNA mapping associated with miRNA sequence variation (isomiR) and RNA editing, and the origin of those unmapped reads after screening against all endogenous reference sequence databases.

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USAGP

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

Cis-antisense gene pairs (CASGPs) can transcribe mRNAs from an opposite strand of a given locus. To classify and understand diverse CASGP phenomena in the human we compiled a genome-wide catalog of CASGPs and integrated these sequences with microarray, SAGE and miRNA data. Using the concept of overlapping regions and clustering of SA transcripts by chromosome coordinates, we identified up to 9000 overlapping antisense loci. Four thousand three hundred and seventy-four of these CASGPs form 1759 complex gene architectures.

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siSPOTR

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

RNA interference (RNAi) serves as a powerful and widely used gene silencing tool for basic biological research and is being developed as a therapeutic avenue to suppress disease-causing genes. However, the specificity and safety of RNAi strategies remains under scrutiny because small inhibitory RNAs (siRNAs) induce off-target silencing. Currently, the tools available for designing siRNAs are biased toward efficacy as opposed to specificity.

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LeARN

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

In the last decade, sequencing projects have led to the development of a number of annotation systems dedicated to the structural and functional annotation of protein-coding genes. These annotation systems manage the annotation of the non-protein coding genes (ncRNAs) in a very crude way, allowing neither the edition of the secondary structures nor the clustering of ncRNA genes into families which are crucial for appropriate annotation of these molecules.

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