Literature DB >> 18485695

Predicting novel RNA-RNA interactions.

Irmtraud M Meyer1.   

Abstract

The purpose of this article is to give a brief, yet concise overview of the current computational methods for predicting novel RNA-RNA interactions, that is interactions whose characteristic features we do not yet know. We start by briefly reviewing experimentally confirmed examples of RNA-RNA interactions before introducing computational methods for predicting RNA-RNA interactions. We will focus primarily on the interactions between different RNA molecules, that is trans RNA-RNA interactions, and will only discuss methods for predicting RNA structure, that is cis-only RNA-RNA interactions, where this helps to gain a better understanding. We conclude by discussing the merits of the different approaches and provide an outlook on probably and desirable future developments in the field.

Mesh:

Substances:

Year:  2008        PMID: 18485695     DOI: 10.1016/j.sbi.2008.03.006

Source DB:  PubMed          Journal:  Curr Opin Struct Biol        ISSN: 0959-440X            Impact factor:   6.809


  5 in total

1.  A comprehensive comparison of general RNA-RNA interaction prediction methods.

Authors:  Daniel Lai; Irmtraud M Meyer
Journal:  Nucleic Acids Res       Date:  2015-12-15       Impact factor: 16.971

2.  Advantages of mixing bioinformatics and visualization approaches for analyzing sRNA-mediated regulatory bacterial networks.

Authors:  Patricia Thébault; Romain Bourqui; William Benchimol; Christine Gaspin; Pascal Sirand-Pugnet; Raluca Uricaru; Isabelle Dutour
Journal:  Brief Bioinform       Date:  2014-12-03       Impact factor: 11.622

Review 3.  On the importance of cotranscriptional RNA structure formation.

Authors:  Daniel Lai; Jeff R Proctor; Irmtraud M Meyer
Journal:  RNA       Date:  2013-11       Impact factor: 4.942

4.  Prokaryotic whole-transcriptome analysis: deep sequencing and tiling arrays.

Authors:  Roland J Siezen; Greer Wilson; Tilman Todt
Journal:  Microb Biotechnol       Date:  2010-03       Impact factor: 5.813

5.  A comprehensive benchmark of RNA-RNA interaction prediction tools for all domains of life.

Authors:  Sinan Ugur Umu; Paul P Gardner
Journal:  Bioinformatics       Date:  2017-04-01       Impact factor: 6.937

  5 in total

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