Literature DB >> 19833701

From consensus structure prediction to RNA gene finding.

Stephan H Bernhart1, Ivo L Hofacker.   

Abstract

Reliable structure prediction is a prerequisite for most types of bioinformatical analysis of RNA. Since the accuracy of structure prediction from single sequences is limited, one often resorts to computing the consensus structure for a set of related RNA sequences. Since functionally important RNA structures are expected to evolve much more slowly than the underlying sequences, the pattern of sequence (co-)variation can be exploited to dramatically improve structure prediction. Since a conserved common structure is only expected when the RNA structure is under selective pressure, consensus structure prediction also provides an ideal starting point for the de novo detection of structured non-coding RNAs. Here, we review different strategies for the prediction of consensus secondary structures, and show how these approaches can be used to predict non-coding RNA genes.

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Year:  2009        PMID: 19833701     DOI: 10.1093/bfgp/elp043

Source DB:  PubMed          Journal:  Brief Funct Genomic Proteomic        ISSN: 1473-9550


  19 in total

1.  Multilign: an algorithm to predict secondary structures conserved in multiple RNA sequences.

Authors:  Zhenjiang Xu; David H Mathews
Journal:  Bioinformatics       Date:  2010-12-30       Impact factor: 6.937

2.  Detecting riboSNitches with RNA folding algorithms: a genome-wide benchmark.

Authors:  Meredith Corley; Amanda Solem; Kun Qu; Howard Y Chang; Alain Laederach
Journal:  Nucleic Acids Res       Date:  2015-01-23       Impact factor: 16.971

3.  Identification of non-coding RNAs with a new composite feature in the Hybrid Random Forest Ensemble algorithm.

Authors:  Supatcha Lertampaiporn; Chinae Thammarongtham; Chakarida Nukoolkit; Boonserm Kaewkamnerdpong; Marasri Ruengjitchatchawalya
Journal:  Nucleic Acids Res       Date:  2014-04-25       Impact factor: 16.971

4.  Using the RNAstructure Software Package to Predict Conserved RNA Structures.

Authors:  David H Mathews
Journal:  Curr Protoc Bioinformatics       Date:  2014-06-17

5.  Generalized centroid estimators in bioinformatics.

Authors:  Michiaki Hamada; Hisanori Kiryu; Wataru Iwasaki; Kiyoshi Asai
Journal:  PLoS One       Date:  2011-02-18       Impact factor: 3.240

6.  Improving the accuracy of predicting secondary structure for aligned RNA sequences.

Authors:  Michiaki Hamada; Kengo Sato; Kiyoshi Asai
Journal:  Nucleic Acids Res       Date:  2010-09-15       Impact factor: 16.971

7.  TurboFold: iterative probabilistic estimation of secondary structures for multiple RNA sequences.

Authors:  Arif O Harmanci; Gaurav Sharma; David H Mathews
Journal:  BMC Bioinformatics       Date:  2011-04-20       Impact factor: 3.169

8.  Sequence-structure relationships in yeast mRNAs.

Authors:  Andrey Chursov; Mathias C Walter; Thorsten Schmidt; Andrei Mironov; Alexander Shneider; Dmitrij Frishman
Journal:  Nucleic Acids Res       Date:  2011-09-27       Impact factor: 16.971

9.  Detecting remote sequence homology in disordered proteins: discovery of conserved motifs in the N-termini of Mononegavirales phosphoproteins.

Authors:  David Karlin; Robert Belshaw
Journal:  PLoS One       Date:  2012-03-05       Impact factor: 3.240

10.  Shape and secondary structure prediction for ncRNAs including pseudoknots based on linear SVM.

Authors:  Rujira Achawanantakun; Yanni Sun
Journal:  BMC Bioinformatics       Date:  2013-01-21       Impact factor: 3.169

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