scholarly journals A comprehensive study of RNA secondary structure alignment algorithms

2016 ◽  
pp. bbw009 ◽  
Author(s):  
Jimmy Ka Ho Chiu ◽  
Yi-Ping Phoebe Chen
Keyword(s):  
Secondary Structure ◽  
Rna Secondary Structure ◽  
Structure Alignment ◽  
Alignment Algorithms ◽  
Comprehensive Study

DSARna: RNA Secondary Structure Alignment Based on Digital Sequence Representation

2020 ◽  
Vol 23 ◽  
Author(s):  
Longjian Gao ◽  
Chengzhen Xu ◽  
Wangan Song ◽  
Feng Xiao ◽  
Xiaomin Wu ◽  
...  
Keyword(s):  
Secondary Structure ◽  
Rna Structure ◽  
Rna Secondary Structure ◽  
High Throughput Sequencing ◽  
Structural Information ◽  
Dynamic Programming Algorithm ◽  
Structure Alignment ◽  
Programming Algorithm ◽  
Structure Information ◽  
Alignment Algorithms

Background: With increasing applications and development of high-throughput sequencing, knowledge of the primary structure of RNA has expanded exponentially. Moreover, the function of RNA is determined by the secondary or higher RNA structure, and similar structures are related to similar functions, such as the secondary clover structure of tRNA. Therefore, RNA structure alignment is an important subject in computational biology and bioinformatics to accurately predict function. However, the traditional RNA structure alignment algorithms have some drawbacks such as high complexity and easy loss of secondary structure information. Objective: To study RNA secondary structure alignment according to the shortcomings of existing secondary structure alignment algorithms and the characteristics of RNA secondary structure. Method: We propose a new digital sequence RNA structure representation algorithm named “DSARna” . Then based on a dynamic programming algorithm, the scoring matrix and binary path matrix are simultaneously constructed. The backtracking path is identified in the path matrix, and the optimal result is predicted according to the path length. Conclusions: Upon comparison with the existing SimTree algorithm through experimental analysis, the proposed method showed higher accuracy and could ensure that the structural information is not easily lost in terms of improved specificity, sensitivity, and the Matthews correlation coefficient.

RNA secondary structure alignment based on an extended binary coding method

2011 ◽  
Vol 111 (5) ◽  
pp. 978-982 ◽  
Author(s):  
Zhi Cao ◽  
Bo Liao ◽  
Renfa Li ◽  
Jiawei Luo ◽  
Wen Zhu
Keyword(s):  
Secondary Structure ◽  
Rna Secondary Structure ◽  
Structure Alignment ◽  
Binary Coding ◽  
Coding Method

A Binary Coding Method for RNA Secondary Structure Alignment

2010 ◽  
Vol 7 (3) ◽  
pp. 619-622
Author(s):  
Xuyu Xiang ◽  
Bo Liao ◽  
Dafang Zhang ◽  
Jiawei Luo
Keyword(s):  
Secondary Structure ◽  
Rna Secondary Structure ◽  
Structure Alignment ◽  
Binary Coding ◽  
Coding Method

SCOT: Rethinking the classification of secondary structure elements

2019 ◽  
Vol 36 (8) ◽  
pp. 2417-2428
Author(s):  
Tobias Brinkjost ◽  
Christiane Ehrt ◽  
Oliver Koch ◽  
Petra Mutzel
Keyword(s):  
Secondary Structure ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
Structural Alignment ◽  
Secondary Structure Element ◽  
Structure Alignment ◽  
Supplementary Information ◽  
Structure Quality ◽  
Alignment Algorithms ◽  
Geometric Consistency

Abstract Motivation Secondary structure classification is one of the most important issues in structure-based analyses due to its impact on secondary structure prediction, structural alignment and protein visualization. There are still open challenges concerning helix and sheet assignments which are currently not addressed by a single multi-purpose software. Results We introduce SCOT (Secondary structure Classification On Turns) as a novel secondary structure element assignment software which supports the assignment of turns, right-handed α-, 310- and π-helices, left-handed α- and 310-helices, 2.27- and polyproline II helices, β-sheets and kinks. We demonstrate that the introduction of helix Purity values enables a clear differentiation between helix classes. SCOT’s unique strengths are highlighted by comparing it to six state-of-the-art methods (DSSP, STRIDE, ASSP, SEGNO, DISICL and SHAFT). The assignment approaches were compared concerning geometric consistency, protein structure quality and flexibility dependency and their impact on secondary structure element-based structural alignments. We show that only SCOT’s combination of hydrogen bonds, geometric criteria and dihedral angles enables robust assignments independent of the structure quality and flexibility. We demonstrate that this combination and the elaborate kink detection lead to SCOT’s clear superiority for protein alignments. As the resulting helices and strands are provided in a PDB conform output format, they can immediately be used for structure alignment algorithms. Taken together, the application of our new method and the straight-forward visualization using the accompanying PyMOL scripts enable the comprehensive analysis of regular backbone geometries in proteins. Availability and implementation https://this-group.rocks Supplementary information Supplementary data are available at Bioinformatics online.

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