Literature DB >> 25726462

Improving RNA secondary structure prediction with structure mapping data.

Michael F Sloma1, David H Mathews2.   

Abstract

Methods to probe RNA secondary structure, such as small molecule modifying agents, secondary structure-specific nucleases, inline probing, and SHAPE chemistry, are widely used to study the structure of functional RNA. Computational secondary structure prediction programs can incorporate probing data to predict structure with high accuracy. In this chapter, an overview of current methods for probing RNA secondary structure is provided, including modern high-throughput methods. Methods for guiding secondary structure prediction algorithms using these data are explained, and best practices for using these data are provided. This chapter concludes by listing a number of open questions about how to best use probing data, and what these data can provide.
© 2015 Elsevier Inc. All rights reserved.

Keywords:  DMS; SHAPE; SNRNASM; Single nucleotide resolution nucleic acid structure mapping experiments

Mesh:

Substances:

Year:  2015        PMID: 25726462     DOI: 10.1016/bs.mie.2014.10.053

Source DB:  PubMed          Journal:  Methods Enzymol        ISSN: 0076-6879            Impact factor:   1.600


  30 in total

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

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5.  SEQualyzer: interactive tool for quality control and exploratory analysis of high-throughput RNA structural profiling data.

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Journal:  Bioinformatics       Date:  2017-02-01       Impact factor: 6.937

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8.  Modeling RNA secondary structure folding ensembles using SHAPE mapping data.

Authors:  Aleksandar Spasic; Sarah M Assmann; Philip C Bevilacqua; David H Mathews
Journal:  Nucleic Acids Res       Date:  2018-01-09       Impact factor: 16.971

Review 9.  Biochemical Methods To Investigate lncRNA and the Influence of lncRNA:Protein Complexes on Chromatin.

Authors:  Emily J McFadden; Amanda E Hargrove
Journal:  Biochemistry       Date:  2016-02-24       Impact factor: 3.162

10.  Bridging the gap between in vitro and in vivo RNA folding.

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Journal:  Q Rev Biophys       Date:  2016-06-24       Impact factor: 5.318

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