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Related Concept Videos

RNA-seq03:21

RNA-seq

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 microarray-based...
RNA Structure01:23

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 Structure01:19

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...
RNA Structure01:23

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...
Nucleic Acid Structure01:25

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 has a double-helix structure. The...
Ribosome Profiling02:24

Ribosome Profiling

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 helps...

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Updated: May 31, 2026

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells
10:34

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

Published on: December 9, 2022

A conditional random fields method for RNA sequence-structure relationship modeling and conformation sampling.

Zhiyong Wang1, Jinbo Xu

  • 1Toyota Technological Institute at Chicago, IL, USA. zywang@ttic.edu

Bioinformatics (Oxford, England)
|June 21, 2011
PubMed
Summary
This summary is machine-generated.

Predicting non-coding RNA tertiary structures is challenging. A new TreeFolder method using conditional random fields (CRFs) models sequence-structure relationships, improving RNA conformation sampling and generating more native-like structures.

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Related Experiment Videos

Last Updated: May 31, 2026

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells
10:34

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

Published on: December 9, 2022

RNA Secondary Structure Prediction Using High-throughput SHAPE
13:42

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

Comparative RNA Structure Analysis of Nascent and Mature Transcripts in Saccharomyces cerevisiae
09:12

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

Published on: February 27, 2026

Area of Science:

  • Computational biology
  • Structural bioinformatics
  • Molecular modeling

Background:

  • Accurate RNA tertiary structures are crucial for understanding non-coding RNA function.
  • Predicting these structures is difficult due to vast conformational spaces and inadequate scoring functions.
  • Existing methods like FARNA and BARNACLE have limitations in representing conformations and incorporating sequence information.

Purpose of the Study:

  • To develop a novel method for accurate RNA tertiary structure prediction.
  • To effectively model the RNA sequence-structure relationship for improved conformation sampling.
  • To enhance the generation of native-like RNA decoys compared to existing approaches.

Main Methods:

  • Developed a probabilistic graphical model using conditional random fields (CRFs) to learn RNA sequence-structure relationships.
  • Integrated CRFs with a novel tree-guided sampling scheme for RNA conformation sampling.
  • Applied the TreeFolder method to predict RNA tertiary structures.

Main Results:

  • The CRF model accurately captures the RNA sequence-structure relationship.
  • Sequence information significantly improves RNA conformation sampling.
  • TreeFolder generates a substantially higher percentage of native-like decoys than FARNA and BARNACLE.

Conclusions:

  • Conditional random fields provide an effective approach for modeling RNA sequence-structure relationships.
  • The TreeFolder method, incorporating sequence information, advances RNA tertiary structure prediction.
  • This approach enhances the accuracy and efficiency of identifying functional RNA structures.