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Comparison of Pseudoknotted RNA Secondary Structures by Topological Centroid Identification and Tree Edit Distance.

Authors :
Wang, Feiqi
Akutsu, Tatsuya
Mori, Tomoya
Source :
Journal of Computational Biology. Sep2020, Vol. 27 Issue 9, p1443-1451. 9p.
Publication Year :
2020

Abstract

Comparison of RNA structures is one of the most crucial analysis for elucidating their individual functions and promoting medical applications. Because it is widely accepted that their functions and structures are strongly correlated, various methods for RNA secondary structure analysis have been proposed owing to the difficulty in predicting RNA three-dimensional structure directly from its sequence. However, there are few methods dealing with RNA secondary structures with a specific and complex partial structure called pseudoknot despite its significance to biological process, which is a big obstacle for analyzing their functions. In this study, we propose a novel tree representation of pseudoknotted RNA secondary structures by topological centroid identification and their comparison methods based on the tree edit distance. In the proposed method, a given graph representing an RNA secondary structure is transformed to a tree rooted at one of the vertices constituting the topological centroid that is identified by removing cycles with peeling processing for the graph. When comparing tree-represented RNA secondary structures collected from a public database using the tree edit distance and functional gene groups defined by Gene Ontology (GO), the proposed method showed better clustering results according to their GOs than canonical RNA sequence-based comparison. In addition, we also report a case that the combination of the tree edit distance and the sequence edit distance shows a better classification of the pseudoknotted RNA secondary structures. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10665277
Volume :
27
Issue :
9
Database :
Academic Search Index
Journal :
Journal of Computational Biology
Publication Type :
Academic Journal
Accession number :
145731002
Full Text :
https://doi.org/10.1089/cmb.2019.0512