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Related Experiment Video

Updated: Sep 22, 2025

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells

Published on: December 9, 2022

Computational Approaches for RNA Structure Ensemble Deconvolution from Structure Probing Data.

Sharon Aviran¹, Danny Incarnato²

¹Biomedical Engineering Department and Genome Center, University of California, Davis, CA, USA.

Journal of Molecular Biology

|May 20, 2022

Summary

This summary is machine-generated.

RNA structure probing reveals dynamic molecular structures. New computational methods reconstruct alternative RNA conformations, enabling the study of RNA structure ensembles in living cells.

Keywords:

RNA structure ensemble SHAPE clustering partition function thermodynamics

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Practical Aspects of Sample Preparation and Setup of 1H R1ρ Relaxation Dispersion Experiments of RNA

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Published on: July 9, 2021

Area of Science:

Molecular Biology
Biophysics
Computational Biology

Background:

RNA structure probing is a key technique for determining RNA molecular structures.
RNA molecules can exist in multiple conformations simultaneously, complicating data interpretation.
Studying RNA structure ensembles is crucial for understanding cellular functions.

Purpose of the Study:

To review computational methods for reconstructing alternative RNA conformations from probing data.
To discuss the challenges and limitations of current methods.
To explore future improvements in RNA structure ensemble analysis.

Main Methods:

Analysis of RNA structure probing data.
Development and application of computational algorithms.
Critical evaluation of existing methodologies.

Main Results:

Computational methods can reconstruct coexisting alternative RNA conformations.
These methods facilitate the study of RNA structure ensembles.
Current approaches have limitations that require further development.

Conclusions:

Computational reconstruction of RNA structure ensembles is advancing.
Further improvements are needed for robust analysis in cellular contexts.
This field holds promise for understanding dynamic RNA biology.