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RNA Structure

RNA Structure

No description available

RNA Structure

RNA Structure

Overview
The basic structure of RNA consists of a five-carbon sugar and one of four nitrogenous bases. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
There are three main types of ribonucleic acid (RNA): messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three RNA types consist of a...

RNA Structure

RNA Structure

The basic structure of RNA consists of a string of ribonucleotides attached by phosphodiester bonds. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
There are three main types of ribonucleic acid (RNA) involved in protein synthesis: messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three...

Nucleic Acid Structure

Nucleic Acid Structure

The pentose sugar in DNA is deoxyribose, while in RNA the pentose sugar is ribose. The difference between the sugars is the presence of the hydroxyl group on the ribose's second carbon and a hydrogen on the deoxyribose's second carbon. The phosphate residue attaches to the hydroxyl group of the 5′ carbon of one sugar and the hydroxyl group of the 3′ carbon of the sugar of the next nucleotide, which forms a 5′ to 3′ phosphodiester linkage.
DNA Structure
DNA...

RNA Stability

RNA Stability

Intact DNA strands can be found in fossils, while scientists sometimes struggle to keep RNA intact under laboratory conditions. The structural variations between RNA and DNA underlie the differences in their stability and longevity. Because DNA is double-stranded, it is inherently more stable. The single-stranded structure of RNA is less stable but also more flexible and can form weak internal bonds. Additionally, most RNAs in the cell are relatively short, while DNA can be up to 250 million...

RNA Stability

RNA Stability

No description available

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Related Experiment Video

Updated: Mar 31, 2026

Comparative RNA Structure Analysis of Nascent and Mature Transcripts in Saccharomyces cerevisiae

Comparative RNA Structure Analysis of Nascent and Mature Transcripts in Saccharomyces cerevisiae

Published on: February 27, 2026

Template-based RNA structure prediction advanced through a blind code competition.

Youhan Lee¹, Shujun He², Toshiyuki Oda³

¹NVIDIA, USA.

Biorxiv : the Preprint Server for Biology

|January 9, 2026

Summary

This summary is machine-generated.

A Kaggle competition on RNA 3D structure prediction revealed a top strategy using 3D templates, not deep learning. Integrating this approach improved RNA structure prediction accuracy.

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Last Updated: Mar 31, 2026

Comparative RNA Structure Analysis of Nascent and Mature Transcripts in Saccharomyces cerevisiae

Comparative RNA Structure Analysis of Nascent and Mature Transcripts in Saccharomyces cerevisiae

Published on: February 27, 2026

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

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RNA Secondary Structure Prediction Using High-throughput SHAPE

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

Area of Science:

Computational Biology
Structural Biology
Bioinformatics

Background:

Predicting RNA 3D structure from sequence is a significant challenge.
Existing methods often struggle with accuracy and scalability.

Purpose of the Study:

To evaluate novel approaches for RNA 3D structure prediction.
To identify effective strategies from a large-scale computational challenge.

Main Methods:

A Kaggle competition involving over 1700 teams and 43 new RNA structures.
Development and integration of top-performing algorithms, including a template-modeling pipeline.
Creation of a unified model (RNAPro) combining successful strategies.

Main Results:

Top algorithms achieved accuracy comparable to leading structure prediction efforts.
A template-based modeling pipeline, surprisingly without deep learning, emerged as a top strategy.
The integrated RNAPro model outperformed individual competition models on the same dataset.

Conclusions:

Template-based modeling is increasingly important for RNA structure prediction.
Large-scale competitions can drive significant advancements in computational biology.
Combining diverse strategies can lead to superior predictive models.