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RNA dot plots: an image representation for RNA secondary structure analysis and manipulations
Author(s) -
Churkin Alexander,
Barash Danny
Publication year - 2013
Publication title -
wiley interdisciplinary reviews: rna
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.225
H-Index - 71
eISSN - 1757-7012
pISSN - 1757-7004
DOI - 10.1002/wrna.1154
Subject(s) - nucleic acid secondary structure , protein secondary structure , rna , representation (politics) , similarity (geometry) , folding (dsp implementation) , algorithm , computer science , string (physics) , nucleic acid structure , computational biology , biological system , artificial intelligence , biology , image (mathematics) , mathematics , engineering , gene , genetics , mathematical physics , biochemistry , electrical engineering , politics , political science , law
Dot plots were originally introduced in bioinformatics as dot‐containing images used to compare biological sequences and identify regions of close similarity between them. In addition to similarity, dot plots were extended to possibly represent interactions between building blocks of biological sequences, where the dots can vary in size or color according to desired features. In this survey, we first review their use in representing an RNA secondary structure, which has mostly been applied for displaying the output secondary structures as a result of running RNA folding prediction algorithms. Such a result may often contain suboptimal solutions in addition to the optimal one, which can be easily incorporated in the dot plot. We then proceed from their passive use of providing RNA secondary structure snapshots to their active use of illustrating RNA secondary structure manipulations in beneficial ways. While comparison between RNA secondary structures can mostly be done efficiently using a string representation, there are notable advantages in using dot plots for analyzing the suboptimal solutions that convey important information about the structure of the RNA molecule. In addition, structure‐based alignment of dot plots has been advanced considerably and the filtering of dot plots that considers chemical and enzymatic data from structure determination experiments has been suggested. We discuss these procedures and how they can be enhanced in the future by using an image representation to analyze RNA secondary structures and examine their manipulations. WIREs RNA 2013, 4:205–216. doi: 10.1002/wrna.1154 This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA

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