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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. 
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RNA Structure01:19

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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
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Related Experiment Video

Updated: Jun 25, 2026

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

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

An image processing approach to computing distances between RNA secondary structures dot plots.

Tor Ivry1, Shahar Michal, Assaf Avihoo

  • 1Department of Computer Science, Ben-Gurion University, Beersheba, Israel. ivryt@cs.bgu.ac.il

Algorithms for Molecular Biology : AMB
|February 11, 2009
PubMed
Summary
This summary is machine-generated.

We developed DoPloCompare, a novel method for comparing RNA secondary structures using dot plot images. This image-processing-based approach enhances RNA design and mutation detection by accurately measuring structural similarity.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Comparing RNA secondary structures is crucial for understanding their function and identifying related structures within databases.
  • Existing methods for RNA structure comparison primarily use string or graph representations, neglecting the visual information present in dot plots.
  • Dot plots, as digital images, offer a unique opportunity for applying image processing techniques to RNA structure analysis.

Purpose of the Study:

  • To introduce a new metric, DoPloCompare, for quantifying the distance between RNA secondary structures based on their dot plot representations.
  • To leverage image processing techniques for a more effective comparison of RNA secondary structures.
  • To demonstrate the utility of DoPloCompare in practical bioinformatics applications.

Main Methods:

  • Developed DoPloCompare, a novel metric that compares RNA secondary structures by analyzing their dot plot diagrams.
  • The metric combines histogram correlations and geometrical distance measures, inspired by image processing methodologies.
  • Applied the metric to two distinct problems: RNA design and the identification of point mutations causing significant structural alterations.

Main Results:

  • DoPloCompare was successfully applied to RNA design, outperforming existing methods in finding nucleotide sequences for given secondary structures.
  • The metric effectively identified peculiar point mutations that induce substantial conformational changes compared to wild-type structures.
  • Validation on ribosomal RNA pieces showed DoPloCompare's predictive accuracy aligns well with experimentally derived structures, surpassing standard comparison methods.

Conclusions:

  • Introduced DoPloCompare, a novel, image processing-inspired metric for comparing RNA secondary structures represented as dot plots.
  • Demonstrated the metric's effectiveness in addressing the RNA design challenge.
  • Showcased the application of DoPloCompare in detecting conformational changes induced by point mutations in RNA sequences.