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Related Concept Videos

RNA Editing02:23

RNA Editing

RNA editing is a post-transcriptional modification where a precursor mRNA (pre-mRNA) nucleotide sequence is changed by base insertion, deletion, or modification. The extent of RNA editing varies from a few hundred bases, in mitochondrial DNA of trypanosomes, to a just single base, in nuclear genes of mammals. Even a single base change in the pre-mRNA can convert a codon for one amino acid into the codon for another amino acid or a stop codon. This type of re-coding can significantly affect the...
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The Upf proteins that carry out nonsense-mediated decay (NMD) are found in all eukaryotic organisms, including humans. Each protein has an individual role, but they need to work in collaboration. Upf1 is an ATP-dependent RNA helicase that unwinds the RNA helix. Because Upf1 can unwind any RNA, Upf2 and Upf3 are required to help Upf1 discriminate between nonsense and normal mRNAs.
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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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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.
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A Nonsequencing Approach for the Rapid Detection of RNA Editing
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Published on: April 21, 2022

Improved algorithms for parsing ESLTAGs: a grammatical model suitable for RNA pseudoknots.

Sanguthevar Rajasekaran1, Sahar Al Seesi, Reda A Ammar

  • 1Computer Science and Engineering Department, University of Connecticut, 371 Fairfield Rd., Unit 2155, Storrs, CT 06269-2155, USA. rajasek@engr.uconn.edu

IEEE/ACM Transactions on Computational Biology and Bioinformatics
|May 26, 2010
PubMed
Summary

Efficient parsing algorithms for Simple Linear Tree Adjoining Grammars (SLTAGs) and Extended SLTAGs (ESLTAGs) were developed. These new algorithms improve RNA structure prediction by offering better performance than existing methods.

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Formal Language Theory

Background:

  • Formal grammars are crucial for modeling biological systems, particularly RNA structures.
  • Simple Linear Tree Adjoining Grammars (SLTAGs) and Extended SLTAGs (ESLTAGs) are key formalisms for RNA structure analysis.
  • The efficiency of parsing algorithms directly impacts the performance of grammar-based biological modeling techniques.

Purpose of the Study:

  • To develop and present efficient parsing algorithms for SLTAGs and ESLTAGs.
  • To improve the computational efficiency of RNA structure prediction using formal grammars.

Main Methods:

  • Developed novel parsing algorithms for SLTAGs and ESLTAGs.
  • Analyzed the time and space complexity of the proposed algorithms, achieving O(min{m,n⁴}).
  • Compared the practical performance of the new algorithms against existing methods, including those by Uemura et al.

Main Results:

  • The proposed algorithms for SLTAGs and ESLTAGs parsing demonstrate an efficient time and space complexity of O(min{m,n⁴}).
  • Empirical results indicate that the new algorithms outperform the algorithms developed by Uemura et al. in practice.
  • The developed algorithms provide a more efficient approach to parsing grammars used in RNA structure modeling.

Conclusions:

  • The presented efficient parsing algorithms for SLTAGs and ESLTAGs offer significant practical performance improvements.
  • These advancements contribute to more effective computational tools for RNA structure prediction and analysis.
  • The study highlights the importance of algorithmic efficiency in the application of formal grammars to biological problems.