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Related Concept Videos

RNA Structure01:19

RNA Structure

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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.
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ER is the primary site for the maturation and folding of soluble and transmembrane secretory proteins. The calnexin cycle is a specific chaperone system that folds and assesses the confirmation of N-glycosylated proteins before they can exit the ER lumen. The primary players of this quality check pipeline are the lectins, ER-resident chaperones, and a glucosyl transferase enzyme. In case the calnexin system in the lumen fails to salvage a misfolded protein, it is transported to the cytoplasm...
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Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

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Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
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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.
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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.
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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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Updated: Oct 4, 2025

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

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Efficient Generation of RNA Secondary Structure Prediction Algorithm Under PAR Framework.

Haihe Shi1, Xiaoqian Jing1

  • 1School of Computer and Information Engineering, Jiangxi Normal University, Nanchang, China.

Frontiers in Plant Science
|February 7, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel dynamic programming approach for RNA secondary structure prediction, enhancing efficiency and reliability in bioinformatics research. The new method streamlines algorithm development for genomic analysis.

Keywords:
PAR platformRNA secondary structure prediction algorithmalgorithm component libraryfeature modelinggenerative programming

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • RNA secondary structure prediction is crucial for understanding genetic processes.
  • Existing algorithms face challenges with time, space, and data complexity.

Purpose of the Study:

  • To analyze and model the domain of dynamic programming-based RNA secondary structure prediction (DP-SSP).
  • To develop a more efficient and reliable DP-SSP algorithm using generative programming.

Main Methods:

  • In-depth analysis and domain feature modeling of DP-SSP.
  • Interactive design of DP-SSP algorithm components via generative programming.
  • Formal realization of a DP-SSP component library using the PAR platform.

Main Results:

  • A formally realized component library for DP-SSP algorithms.
  • Generation of concrete algorithms through component assembly.
  • Demonstrated improvement in the efficiency and reliability of RNA secondary structure prediction algorithm development.

Conclusions:

  • The generative programming approach offers a robust method for developing DP-SSP algorithms.
  • Component-based development enhances efficiency and reliability in bioinformatics tool creation.
  • This work contributes to advancing RNA secondary structure prediction methodologies.