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Related Concept Videos

RNA Structure01:19

RNA Structure

7.9K
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...
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RNA Structure01:23

RNA Structure

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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...
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RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
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RNA Stability01:53

RNA Stability

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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...
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Ribosome Profiling02:24

Ribosome Profiling

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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
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Nucleic Acid Structure01:25

Nucleic Acid Structure

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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...
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Updated: Feb 28, 2026

RNA Secondary Structure Prediction Using High-throughput SHAPE
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RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

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[Research progress in RNA secondary structure prediction methods].

Zezhou Hao1,2, Yanling Yang1,2, Helong Zhao1,2

  • 1School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.

Sheng Wu Gong Cheng Xue Bao = Chinese Journal of Biotechnology
|February 27, 2026
PubMed
Summary
This summary is machine-generated.

Computational biology aids RNA secondary structure prediction, crucial for molecular stability and function. This review compares prediction methods and discusses their biomedical applications, especially identifying RNA-binding protein sites.

Keywords:
RNA secondary structureRNA-binding proteinscomputational biologypredictionstructural biology

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Area of Science:

  • Structural biology
  • Computational biology
  • Biomedical research

Background:

  • RNA secondary structures are vital for molecular stability and biological functions.
  • Experimental determination of RNA structures is complex and expensive.
  • Computational methods offer efficient alternatives for RNA structure prediction.

Purpose of the Study:

  • To review computational methods for RNA secondary structure prediction.
  • To compare the advantages and disadvantages of various prediction algorithms.
  • To discuss the biomedical applications of these prediction techniques, focusing on RNA-binding protein site identification.

Main Methods:

  • Energy-based methods
  • Multiple-sequence methods
  • Traditional machine learning methods
  • Deep learning methods
  • Tertiary structure-based methods

Main Results:

  • Comparison of strengths and weaknesses of different computational approaches.
  • Identification of key applications in biomedical fields.
  • Highlighting the role of RNA secondary structure prediction in identifying RNA-binding protein sites.

Conclusions:

  • Computational methods are essential for accurate RNA secondary structure prediction.
  • These methods have significant implications for biomedical research, particularly in understanding RNA-protein interactions.
  • Future developments will further enhance prediction accuracy and applications.