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Related Concept Videos

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 Structure01:23

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...
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...
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...
Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...

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Related Experiment Video

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

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

RNAalifold: improved consensus structure prediction for RNA alignments.

Stephan H Bernhart1, Ivo L Hofacker, Sebastian Will

  • 1Department of Computer Science, University of Leipzig, Leipzig, Germany. berni@tbi.univie.ac.at

BMC Bioinformatics
|November 19, 2008
PubMed
Summary
This summary is machine-generated.

This study enhances RNAalifold, a tool for predicting RNA consensus structures. New methods improve accuracy and efficiency, making it competitive with other RNA structure prediction tools.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Biology

Background:

  • RNA structure prediction is crucial for analyzing RNA function.
  • RNAalifold is a long-standing tool for predicting consensus RNA structures from aligned sequences.
  • Existing RNAalifold methods have limitations that newer approaches aim to address.

Purpose of the Study:

  • To improve the accuracy and efficiency of RNA structure prediction using RNAalifold.
  • To introduce enhanced gap handling and scoring matrices into the RNAalifold algorithm.
  • To compare the performance of the improved RNAalifold against existing tools.

Main Methods:

  • Implementing improved alignment gap handling in RNAalifold.
  • Replacing simplistic covariance scoring with RIBOSUM-like matrices.
  • Evaluating the enhanced RNAalifold on diverse RNA sequence datasets.

Main Results:

  • Substantial improvements in RNAalifold prediction accuracy were achieved.
  • The enhanced RNAalifold maintains computational efficiency.
  • The new RNAalifold version outperforms the original and several other contemporary tools.

Conclusions:

  • The revised RNAalifold offers superior performance for RNA consensus structure prediction.
  • The updated tool is a viable replacement for the original RNAalifold in most applications.
  • The enhanced RNAalifold is competitive with advanced methods like SCFGs and hierarchical classifiers.