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Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA
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Structural relation matching: an algorithm to identify structural patterns into RNAs and their interactions.

Michela Quadrini1

  • 1University of Camerino, School of Science and Technology, via Madonna delle Carceri, Camerino, Italy.

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|May 29, 2021
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Summary
This summary is machine-generated.

This study introduces a novel Python-based algorithm to identify RNA structural patterns, including complex pseudoknots, by analyzing RNA secondary structures and their interactions. The method efficiently quantifies the impact of inhibitors on RNA structures.

Keywords:
coreloopsrelation matrixrelationsshapestructural pattern

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Area of Science:

  • Computational Biology
  • Molecular Biology
  • Bioinformatics

Background:

  • RNA molecules are vital for biological processes, with their function dictated by 3D structures and interactions.
  • RNA secondary structures, including cores and shadows, can be represented as arc diagrams, which may contain pseudoknots.

Purpose of the Study:

  • To develop and implement algorithms for identifying structural patterns in RNA secondary structures and RNA-RNA interactions, accommodating arbitrary pseudoknots.
  • To map these abstractions into matrices representing loop relations for efficient analysis.

Main Methods:

  • Formalizing RNA secondary structures and RNA-RNA interactions as arc diagrams, including pseudoknotted structures.
  • Developing polynomial-time algorithms implemented in Python to identify structural patterns using matrix and submatrix analysis.
  • Applying the approach to analyze 16S ribosomal RNAs from *Thermus thermophilus* in the presence of inhibitors.

Main Results:

  • The study successfully implemented algorithms to detect structural patterns in RNA secondary structures and RNA-RNA interactions, handling pseudoknots.
  • The approach was validated on 16S ribosomal RNAs, quantifying the structural effects of inhibitors.

Conclusions:

  • The developed matrix-based approach provides an efficient method for identifying complex RNA structural patterns, including those with pseudoknots.
  • This technique is valuable for understanding RNA-ligand interactions and the functional impact of inhibitors.