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Related Experiment Video

Updated: Apr 16, 2026

RNA Secondary Structure Prediction Using High-throughput SHAPE

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

Improving RNA secondary structure prediction with structure mapping data.

Michael F Sloma¹, David H Mathews¹

¹Department of Biochemistry & Biophysics, University of Rochester Medical Center, Box 712, Rochester, New York, USA; Center for RNA Biology, University of Rochester Medical Center, Box 712, Rochester, New York, USA.

Methods in Enzymology

|March 2, 2015

Summary

This summary is machine-generated.

This chapter details RNA secondary structure probing methods and their use in computational predictions. It explains how to integrate probing data for accurate RNA structure analysis and highlights future research directions.

Keywords:

DMS SHAPE SNRNASM Single nucleotide resolution nucleic acid structure mapping experiments

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Area of Science:

Molecular Biology
Biochemistry
Bioinformatics

Background:

Functional RNA molecules rely on specific secondary structures for their biological roles.
Experimental methods are crucial for determining RNA secondary structures.
Computational tools aid in predicting and refining RNA structures.

Purpose of the Study:

To provide a comprehensive overview of current RNA secondary structure probing techniques.
To explain how experimental probing data can guide computational structure prediction.
To discuss best practices and open questions in utilizing probing data.

Main Methods:

Overview of established methods: small molecule modification, nucleases, inline probing, and SHAPE chemistry.
Introduction to modern high-throughput probing technologies.
Explanation of algorithms integrating probing data into secondary structure prediction.

Main Results:

Probing data significantly enhances the accuracy of computational RNA secondary structure predictions.
High-throughput methods offer scalable approaches to structural analysis.
Established best practices facilitate effective data integration.

Conclusions:

RNA probing is essential for understanding RNA function and improving structure prediction accuracy.
Further research is needed to optimize the use of probing data and explore its full potential.
Integrating experimental and computational approaches is key to advancing RNA structural biology.