Literature DB >> 24639155

Energy-directed RNA structure prediction.

Ivo L Hofacker1.   

Abstract

In this chapter we present the classic dynamic programming algorithms for RNA structure prediction by energy minimization, as well as variations of this approach that allow to compute suboptimal foldings, or even the partition function over all possible secondary structures. The latter are essential in order to deal with the inaccuracy of minimum free energy (MFE) structure prediction, and can be used, for example, to derive reliability measures that assign a confidence value to all or part of a predicted structure. In addition, we discuss recently proposed alternatives to the MFE criterion such as the use of maximum expected accuracy (MEA) or centroid structures. The dynamic programming algorithms implicitly assume that the RNA molecule is in thermodynamic equilibrium. However, especially for long RNAs, this need not be the case. In the last section we therefore discuss approaches for predicting RNA folding kinetics and co-transcriptional folding.

Mesh:

Substances:

Year:  2014        PMID: 24639155     DOI: 10.1007/978-1-62703-709-9_4

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  11 in total

1.  Modeling RNA Secondary Structure with Sequence Comparison and Experimental Mapping Data.

Authors:  Zhen Tan; Gaurav Sharma; David H Mathews
Journal:  Biophys J       Date:  2017-07-20       Impact factor: 4.033

2.  TurboFold II: RNA structural alignment and secondary structure prediction informed by multiple homologs.

Authors:  Zhen Tan; Yinghan Fu; Gaurav Sharma; David H Mathews
Journal:  Nucleic Acids Res       Date:  2017-11-16       Impact factor: 16.971

Review 3.  How to benchmark RNA secondary structure prediction accuracy.

Authors:  David H Mathews
Journal:  Methods       Date:  2019-04-02       Impact factor: 3.608

4.  Identification of new high affinity targets for Roquin based on structural conservation.

Authors:  Johannes Braun; Sandra Fischer; Zhenjiang Z Xu; Hongying Sun; Dalia H Ghoneim; Anna T Gimbel; Uwe Plessmann; Henning Urlaub; David H Mathews; Julia E Weigand
Journal:  Nucleic Acids Res       Date:  2018-12-14       Impact factor: 16.971

5.  A parallel implementation of the Wuchty algorithm with additional experimental filters to more thoroughly explore RNA conformational space.

Authors:  Jonathan W Stone; Samuel Bleckley; Sean Lavelle; Susan J Schroeder
Journal:  PLoS One       Date:  2015-02-19       Impact factor: 3.240

6.  Analysis of RNA nearest neighbor parameters reveals interdependencies and quantifies the uncertainty in RNA secondary structure prediction.

Authors:  Jeffrey Zuber; B Joseph Cabral; Iain McFadyen; David M Mauger; David H Mathews
Journal:  RNA       Date:  2018-08-13       Impact factor: 4.942

7.  Estimating uncertainty in predicted folding free energy changes of RNA secondary structures.

Authors:  Jeffrey Zuber; David H Mathews
Journal:  RNA       Date:  2019-04-05       Impact factor: 4.942

8.  Swellix: a computational tool to explore RNA conformational space.

Authors:  Nathan Sloat; Jui-Wen Liu; Susan J Schroeder
Journal:  BMC Bioinformatics       Date:  2017-11-21       Impact factor: 3.169

Review 9.  Viroid research and its significance for RNA technology and basic biochemistry.

Authors:  Gerhard Steger; Detlev Riesner
Journal:  Nucleic Acids Res       Date:  2018-11-16       Impact factor: 16.971

10.  Secondary structure prediction for RNA sequences including N6-methyladenosine.

Authors:  Elzbieta Kierzek; Xiaoju Zhang; Richard M Watson; Scott D Kennedy; Marta Szabat; Ryszard Kierzek; David H Mathews
Journal:  Nat Commun       Date:  2022-03-11       Impact factor: 17.694

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