RNA structure prediction.

The prediction of RNA structure can be a first important step for the functional characterization of novel ncRNAs. Especially for the very meaningful secondary structure, there is a multitude of computational prediction tools. They differ not only in algorithmic details and the underlying models but also in what exactly they are trying to predict. This chapter gives an overview of different programs that aim to predict RNA secondary structure. We will introduce the ViennaRNA software package and web server as a solution that implements most of the varieties of RNA secondary structure prediction that have been published over the years. We focus on algorithms going beyond the mere prediction of a static structure.

[1]  J. Sabina,et al.  Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure. , 1999, Journal of molecular biology.

[2]  Kiyoshi Asai,et al.  CentroidFold: a web server for RNA secondary structure prediction , 2009, Nucleic Acids Res..

[3]  Ronny Lorenz,et al.  The Vienna RNA Websuite , 2008, Nucleic Acids Res..

[4]  Michael Zuker,et al.  UNAFold: software for nucleic acid folding and hybridization. , 2008, Methods in molecular biology.

[5]  I. Hofacker,et al.  Beyond energy minimization: approaches to the kinetic folding of RNA , 2008 .

[6]  Michael Zuker,et al.  Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information , 1981, Nucleic Acids Res..

[7]  K. Katoh,et al.  MAFFT version 5: improvement in accuracy of multiple sequence alignment , 2005, Nucleic acids research.

[8]  P. Schuster,et al.  Complete suboptimal folding of RNA and the stability of secondary structures. , 1999, Biopolymers.

[9]  D. Turner,et al.  Incorporating chemical modification constraints into a dynamic programming algorithm for prediction of RNA secondary structure. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[10]  Stinus Lindgreen,et al.  WAR: Webserver for aligning structural RNAs , 2008, Nucleic Acids Res..

[11]  Serafim Batzoglou,et al.  CONTRAfold: RNA secondary structure prediction without physics-based models , 2006, ISMB.

[12]  R. Durbin,et al.  RNA sequence analysis using covariance models. , 1994, Nucleic acids research.

[13]  Ye Ding,et al.  Structure clustering features on the Sfold Web server , 2005, Bioinform..

[14]  Rodrigo Lopez,et al.  Clustal W and Clustal X version 2.0 , 2007, Bioinform..

[15]  Kevin P. Murphy,et al.  Efficient parameter estimation for RNA secondary structure prediction , 2007, ISMB/ECCB.

[16]  Stefan L Ameres,et al.  The impact of target site accessibility on the design of effective siRNAs , 2008, Nature Biotechnology.

[17]  J. McCaskill The equilibrium partition function and base pair binding probabilities for RNA secondary structure , 1990, Biopolymers.