Literature DB >> 22336709

Non-coding transcription characterization and annotation: a guide and web resource for non-coding RNA databases.

Alexandre Rossi Paschoal1, Vinicius Maracaja-Coutinho, João Carlos Setubal, Zilá Luz Paulino Simões, Sergio Verjovski-Almeida, Alan Mitchell Durham.   

Abstract

Large-scale transcriptome projects have shown that the number of RNA transcripts not coding for proteins (non-coding RNAs) is much larger than previously recognized. High-throughput technologies, coupled with bioinformatics approaches, have produced increasing amounts of data, highlighting the role of non-coding RNAs (ncRNAs) in biological processes. Data generated by these studies include diverse non-coding RNA classes from organisms of different kingdoms, which were obtained using different experimental and computational assays. This has led to a rapid increase of specialized RNA databases. The fast growth in the number of available databases makes integration of stored information a difficult task. We present here NRDR, a Non-coding RNA Databases Resource for information retrieval on ncRNA databases (www.ncrnadatabases.org). We performed a survey of 102 public databases on ncRNAs and we have introduced four categorizations to classify these databases and to help researchers quickly search and find the information they need: RNA family, information source, information content and available search mechanisms. NRDR is a useful databases searching tool that will facilitate research on ncRNAs.

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Year:  2012        PMID: 22336709     DOI: 10.4161/rna.19352

Source DB:  PubMed          Journal:  RNA Biol        ISSN: 1547-6286            Impact factor:   4.652


  16 in total

Review 1.  Epigenetics and the modulation of neuroinflammation.

Authors:  Gwenn A Garden
Journal:  Neurotherapeutics       Date:  2013-10       Impact factor: 7.620

2.  MicroRNA Databases and Tools.

Authors:  Tharcísio Soares de Amorim; Daniel Longhi Fernandes Pedro; Alexandre Rossi Paschoal
Journal:  Methods Mol Biol       Date:  2022

3.  Computational Analysis of HTS Data and Its Application in Plant Pathology.

Authors:  Edoardo Piombo; Mukesh Dubey
Journal:  Methods Mol Biol       Date:  2022

4.  Computational Analysis of Transposable Elements and CircRNAs in Plants.

Authors:  Liliane Santana Oliveira; Andressa Caroline Patera; Douglas Silva Domingues; Danilo Sipoli Sanches; Fabricio Martins Lopes; Pedro Henrique Bugatti; Priscila Tiemi Maeda Saito; Vinicius Maracaja-Coutinho; Alan Mitchell Durham; Alexandre Rossi Paschoal
Journal:  Methods Mol Biol       Date:  2021

5.  Perspectives of Long Non-Coding RNAs in Cancer Diagnostics.

Authors:  Eduardo M Reis; Sergio Verjovski-Almeida
Journal:  Front Genet       Date:  2012-03-08       Impact factor: 4.599

6.  microRNAs: short non-coding bullets of gain of function mutant p53 proteins.

Authors:  Sara Donzelli; Sabrina Strano; Giovanni Blandino
Journal:  Oncoscience       Date:  2014-06-07

7.  Mirnacle: machine learning with SMOTE and random forest for improving selectivity in pre-miRNA ab initio prediction.

Authors:  Yuri Bento Marques; Alcione de Paiva Oliveira; Ana Tereza Ribeiro Vasconcelos; Fabio Ribeiro Cerqueira
Journal:  BMC Bioinformatics       Date:  2016-12-15       Impact factor: 3.169

8.  LeishDB: a database of coding gene annotation and non-coding RNAs in Leishmania braziliensis.

Authors:  Felipe Torres; Raúl Arias-Carrasco; José C Caris-Maldonado; Aldina Barral; Vinicius Maracaja-Coutinho; Artur T L De Queiroz
Journal:  Database (Oxford)       Date:  2017-01-01       Impact factor: 3.451

9.  RNAmining: A machine learning stand-alone and web server tool for RNA coding potential prediction.

Authors:  Thaís A R Ramos; Nilbson R O Galindo; Raúl Arias-Carrasco; Cecília F da Silva; Vinicius Maracaja-Coutinho; Thaís G do Rêgo
Journal:  F1000Res       Date:  2021-04-26

10.  High-throughput sequencing of small RNA transcriptomes reveals critical biological features targeted by microRNAs in cell models used for squamous cell cancer research.

Authors:  Patricia Severino; Liliane Santana Oliveira; Natalia Torres; Flavia Maziero Andreghetto; Maria de Fatima Guarizo Klingbeil; Raquel Moyses; Victor Wünsch-Filho; Fabio Daumas Nunes; Monica Beatriz Mathor; Alexandre Rossi Paschoal; Alan Mitchell Durham
Journal:  BMC Genomics       Date:  2013-10-26       Impact factor: 3.969

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