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Classifying Conserved RNA Secondary Structures with Pseudoknots by Vector-Edit Distance

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journal contribution
posted on 20.04.2021, 03:03 by L Huang, Qingfeng Chen, Y Li, C Luo
Secondary structures have been proved to relate with the great functional diversity of RNA. There have been many studies to predict and compare the RNA secondary structures. However, fast and accurate comparison of RNA secondary structures with arbitrary pseudoknots is a challenging issue due to the hidden but important structural properties, such as the distribution of stems and branches. In this paper, we construct a novel RNA secondary structure model called modified adjoining grammars binary tree (BTMGCSP). It can not only represent the complex RNA secondary structure including arbitrary pseudoknots intuitively, but also reserve RNA secondary structure properties. Further, we propose vector-edit distance to measure the structure similarity between BTMGCSP trees converted from RNA sequences and their secondary structures for classifying conserved stem pattern. The experimental results show that our method substantially reduces the memory and time consumption in contrast to previous algorithms, such as O((n/k)2) and O(n/k) for time and space complexity, respectively. In particular, the AUC value of our method achieves 0.949 in PseudoBase.

Funding

This work was supported in part by the National Natural Science Foundation of China under Project 61963004 and Project 61751314, in part by the Key Project of Natural Science Foundation of Guangxi under Grant 2017GXNSFDA198033, and in part by the Key Research and Development Plan of Guangxi under Grant AB17195055.

History

Publication Date

01/01/2021

Journal

IEEE Access

Volume

9

Pagination

32008-32018

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

ISSN

2169-3536

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