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S-MED

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

Human sarcomas are a heterogeneous group of over 50 different malignant tumors for which very few diagnostic markers currently exist. MicroRNA (miRNA) transcript levels have been proposed for use in the diagnosis, classification and prognosis of tumors. Over 700 miRNAs are identified in humans and miRNA are considered attractive candidates for developing novel biomarkers in sarcomas. However, miRNA expression patterns found in sarcomas are poorly understood and no central resource exists to contain this information.

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vHoT

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

Some viruses have been reported to transcribe microRNAs, implying complex relationships between the host and the pathogen at the post-transcriptional level through microRNAs in virus-infected cells. Although many computational algorithms have been developed for microRNA target prediction, few have been designed exclusively to find cellular or viral mRNA targets of viral microRNAs in a user-friendly manner. To address this, we introduce the viral microRNA host target (vHoT) database for predicting interspecies interactions between viral microRNA and host genomes.

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HeteroMirPred

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

An ensemble classifier approach for microRNA precursor (pre-miRNA) classification was proposed based upon combining a set of heterogeneous algorithms including support vector machine (SVM), k-nearest neighbors (kNN) and random forest (RF), then aggregating their prediction through a voting system. Additionally, the proposed algorithm, the classification performance was also improved using discriminative features, self-containment and its derivatives, which have shown unique structural robustness characteristics of pre-miRNAs.

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NOVOMIR

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

MicroRNAs (miRNA) are small regulatory, noncoding RNA molecules that are transcribed as primary miRNAs (pri-miRNA) from eukaryotic genomes. At least in plants, their regulatory activity is mediated through base-pairing with protein-coding messenger RNAs (mRNA) followed by mRNA degradation or translation repression. We describe NOVOMIR, a program for the identification of miRNA genes in plant genomes.

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mrsFAST

Submitted by ChenLiang on Sun, 09/10/2017 - 17:15

Abstract is not available.[1]

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miRNA-regulome

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

MicroRNAs are currently being extensively studied due to their important role as post-transcriptional regulators. During miRNA biogenesis, precursors undergo two cleavage steps performed by Drosha-DGCR8 (Microprocessor) cleaving of pri-miRNA to produce pre-miRNA and Dicer-mediated cleaving to create mature miRNA. Genetic variants within human miRNA regulome have been shown to influence miRNA expression, target interaction and to affect the phenotype.

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p-TAREF

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

miRNAs are ~21 nucleotide long small noncoding RNA molecules, formed endogenously in most of the eukaryotes, which mainly control their target genes post transcriptionally by interacting and silencing them. While a lot of tools has been developed for animal miRNA target system, plant miRNA target identification system has witnessed limited development. Most of them have been centered around exact complementarity match. Very few of them considered other factors like multiple target sites and role of flanking regions.

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Discriminant

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

Computational discovery of microRNAs (miRNA) is based on pre-determined sets of features from miRNA precursors (pre-miRNA). Some feature sets are composed of sequence-structure patterns commonly found in pre-miRNAs, while others are a combination of more sophisticated RNA features. In this work, we analyze the discriminant power of seven feature sets, which are used in six pre-miRNA prediction tools. The analysis is based on the classification performance achieved with these feature sets for the training algorithms used in these tools.

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tfmirloop

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

Transcription factors (TFs) have long been known to be principally activators of transcription in eukaryotes and prokaryotes. The growing awareness of the ubiquity of microRNAs (miRNAs) as suppressive regulators in eukaryotes, suggests the possibility of a mutual, preferential, self-regulatory connectivity between miRNAs and TFs. Here we investigate the connectivity from TFs and miRNAs to other genes and each other using text mining, TF promoter binding site and 6 different miRNA binding site prediction methods.

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PMTED

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

MicroRNAs (miRNAs) are identified in nearly all plants where they play important roles in development and stress responses by target mRNA cleavage or translation repression. MiRNAs exert their functions by sequence complementation with target genes and hence their targets can be predicted using bioinformatics algorithms. In the past two decades, microarray technology has been employed to study genes involved in important biological processes such as biotic response, abiotic response, and specific tissues and developmental stages, many of which are miRNA targets.

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