You are here

Home

Target Prediction

Bioinformatics Resource Manager

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

The Bioinformatics Resource Manager (BRM) is a software environment that provides the user with data management, retrieval and integration capabilities. Designed in collaboration with biologists, BRM simplifies mundane analysis tasks of merging microarray and proteomic data across platforms, facilitates integration of users' data with functional annotation and interaction data from public sources and provides connectivity to visual analytic tools through reformatting of the data for easy import or dynamic launching capability.

Rating: 
Average: 5 (1 vote)

RepTar

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

Computational identification of putative microRNA (miRNA) targets is an important step towards elucidating miRNA functions. Several miRNA target-prediction algorithms have been developed followed by publicly available databases of these predictions. Here we present a new database offering miRNA target predictions of several binding types, identified by our recently developed modular algorithm RepTar. RepTar is based on identification of repetitive elements in 3'-UTRs and is independent of both evolutionary conservation and conventional binding patterns (i.e.

Rating: 
Average: 5 (1 vote)

ProMISe

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

Aberrant microRNA (miRNA) expression is implicated in tumorigenesis. The underlying mechanisms are unclear because the regulations of each miRNA on potentially hundreds of mRNAs are sample specific. We describe a novel approach to inferProbabilisticMiRNA-mRNA Interaction Signature ('ProMISe') from a single pair of miRNA-mRNA expression profile. Our model considers mRNA and miRNA competition as a probabilistic function of the expressed seeds (matches). To demonstrate ProMISe, we extensively exploited The Cancer Genome Atlasdata.

Rating: 
Average: 5 (1 vote)

HomoTarget

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

MiRNAs play an essential role in the networks of gene regulation by inhibiting the translation of target mRNAs. Several computational approaches have been proposed for the prediction of miRNA target-genes. Reports reveal a large fraction of under-predicted or falsely predicted target genes. Thus, there is an imperative need to develop a computational method by which the target mRNAs of existing miRNAs can be correctly identified.

Rating: 
Average: 5 (1 vote)

PARma

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

PARma is a complete data analysis software for AGO-PAR-CLIP experiments to identify target sites of microRNAs as well as the microRNA binding to these sites. It integrates specific characteristics of the experiments into a generative model. The model and a novel pattern discovery tool are iteratively applied to data to estimate seed activity probabilities, cluster confidence scores and to assign the most probable microRNA. Based on differential PAR-CLIP analysis and comparison to RIP-Chip data, we show that PARma is more accurate than existing approaches.

Rating: 
Average: 5 (1 vote)

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.

Rating: 
5
Average: 5 (2 votes)

miRTour

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

MicroRNAs (miRNAs) are important negative regulators of gene expression in plant and animals, which are endogenously produced from their own genes. Computational comparative approach based on evolutionary conservation of mature miRNAs has revealed a number of orthologs of known miRNAs in different plant species. The homology-based plant miRNA discovery, followed by target prediction, comprises several steps, which have been done so far manually.

Rating: 
Average: 5 (1 vote)

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.

Rating: 
Average: 5 (1 vote)

targetS

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

Currently available microRNA (miRNA) target prediction algorithms require the presence of a conserved seed match to the 5' end of the miRNA and limit the target sites to the 3' untranslated regions of mRNAs. However, it has been noted that these requirements may be too stringent, leading to a substantial number of missing targets.

Rating: 
Average: 5 (1 vote)

myMIR

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

miRNA target genes prediction represents a crucial step in miRNAs functional characterization. In this context, the challenging issue remains predictions accuracy and recognition of false positive results. In this article myMIR, a web based system for increasing reliability of miRNAs predicted targets lists, is presented. myMIR implements an integrated pipeline for computing ranked miRNA::target lists and provides annotations for narrowing them down.

Rating: 
Average: 5 (1 vote)

Pages

Subscribe to Target Prediction