Dataset Information

HOCTAR database: a unique resource for microRNA target prediction.

ABSTRACT: microRNAs (miRNAs) are the most abundant class of small RNAs in mammals. They play an important role in regulation of gene expression by inducing mRNA cleavage or translational inhibition. Each miRNA targets an average of 100-200 genes by binding, preferentially, to their 3' UTRs by means of partial sequence complementarity. Most miRNAs are localized within transcriptional units, termed host genes, and show similar expression behavior with respect to their corresponding host genes. Considering the impact of miRNA in the regulation of gene expression and their involvement in a growing number of human disorders, it is vital to develop sensitive computational approaches able to identify miRNA target genes. The HOCTAR database (db) is a publicly available resource collecting ranked list of predicted target genes for 290 intragenic miRNAs annotated in human. HOCTARdb is a unique resource that integrates miRNA target prediction genes and transcriptomic data to score putative miRNA targets looking at the expression behavior of their host genes. We demonstrated, by testing 135 known validated target genes (either at the translational or transcriptional level) for different miRNAs, that the miRNA target prediction lists present in HOCTARdb are highly reliable. Moreover, HOCTARdb associates biological roles to each miRNA-controlled transcriptional network by means of Gene Ontology analysis. This information is easily accessible through a user-friendly query page. The HOCTARdb is available at http://hoctar.tigem.it/. We believe that a detailed relationship between miRNAs and their target genes and a constant update of the information contained in HOCTARdb will provide an extremely valuable resource to assist the researcher in the discovery of miRNA target genes.

SUBMITTER: Gennarino VA

PROVIDER: S-EPMC3113163 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

HOCTAR database: a unique resource for microRNA target prediction.

Gennarino Vincenzo Alessandro VA Sardiello Marco M Mutarelli Margherita M Dharmalingam Gopuraja G Maselli Vincenza V Lago Giampiero G Banfi Sandro S

Gene 20110322 1-2

microRNAs (miRNAs) are the most abundant class of small RNAs in mammals. They play an important role in regulation of gene expression by inducing mRNA cleavage or translational inhibition. Each miRNA targets an average of 100-200 genes by binding, preferentially, to their 3' UTRs by means of partial sequence complementarity. Most miRNAs are localized within transcriptional units, termed host genes, and show similar expression behavior with respect to their corresponding host genes. Considering t ...[more]

PMID: 21435384

Similar Datasets

Project description:BackgroundMicroRNAs (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. Despite their value in assisting research work for plant biologists, miRNA target genes are difficult to access without pre-processing and assistance of necessary analytical and visualization tools because they are embedded in a large body of microarray data that are scattered around in public databases.DescriptionPlant MiRNA Target Expression Database (PMTED) is designed to retrieve and analyze expression profiles of miRNA targets represented in the plethora of existing microarray data that are manually curated. It provides a Basic Information query function for miRNAs and their target sequences, gene ontology, and differential expression profiles. It also provides searching and browsing functions for a global Meta-network among species, bioprocesses, conditions, and miRNAs, meta-terms curated from well annotated microarray experiments. Networks are displayed through a Cytoscape Web-based graphical interface. In addition to conserved miRNAs, PMTED provides a target prediction portal for user-defined novel miRNAs and corresponding target expression profile retrieval. Hypotheses that are suggested by miRNA-target networks should provide starting points for further experimental validation.ConclusionsPMTED exploits value-added microarray data to study the contextual significance of miRNA target genes and should assist functional investigation for both miRNAs and their targets. PMTED will be updated over time and is freely available for non-commercial use at http://pmted.agrinome.org.

Project description:MicroRNAs (miRNAs) are single-stranded non-coding RNAs known to regulate a wide range of cellular processes by silencing the gene expression at the protein and/or mRNA levels. Computational prediction of miRNA targets is essential for elucidating the detailed functions of miRNA. However, the prediction specificity and sensitivity of the existing algorithms are still poor to generate meaningful, workable hypotheses for subsequent experimental testing. Constructing a richer and more reliable training data set and developing an algorithm that properly exploits this data set would be the key to improve the performance current prediction algorithms.A comprehensive training data set is constructed for mammalian miRNAs with its positive targets obtained from the most up-to-date miRNA target depository called miRecords and its negative targets derived from 20 microarray data. A new algorithm SVMicrO is developed, which assumes a 2-stage structure including a site support vector machine (SVM) followed by a UTR-SVM. SVMicrO makes prediction based on 21 optimal site features and 18 optimal UTR features, selected by training from a comprehensive collection of 113 site and 30 UTR features. Comprehensive evaluation of SVMicrO performance has been carried out on the training data, proteomics data, and immunoprecipitation (IP) pull-down data. Comparisons with some popular algorithms demonstrate consistent improvements in prediction specificity, sensitivity and precision in all tested cases. All the related materials including source code and genome-wide prediction of human targets are available at http://compgenomics.utsa.edu/svmicro.html.A 2-stage SVM based new miRNA target prediction algorithm called SVMicrO is developed. SVMicrO is shown to be able to achieve robust performance. It holds the promise to achieve continuing improvement whenever better training data that contain additional verified or high confidence positive targets and properly selected negative targets are available.

Dataset Information

HOCTAR database: a unique resource for microRNA target prediction.

Publications

HOCTAR database: a unique resource for microRNA target prediction.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets