假结
蛋白质二级结构
计算机科学
邻接表
结构母题
核酸二级结构
核糖核酸
代表(政治)
理论计算机科学
算法
计算生物学
生物
政治
基因
生物化学
政治学
法学
作者
Jean-Pierre Séhi Glouzon,Jean-Pierre Perreault,Shengrui Wang
出处
期刊:Bioinformatics
[Oxford University Press]
日期:2017-01-14
卷期号:: btw773-btw773
被引量:5
标识
DOI:10.1093/bioinformatics/btw773
摘要
Comparing ribonucleic acid (RNA) secondary structures of arbitrary size uncovers structural patterns that can provide a better understanding of RNA functions. However, performing fast and accurate secondary structure comparisons is challenging when we take into account the RNA configuration (i.e. linear or circular), the presence of pseudoknot and G-quadruplex (G4) motifs and the increasing number of secondary structures generated by high-throughput probing techniques. To address this challenge, we propose the super-n-motifs model based on a latent analysis of enhanced motifs comprising not only basic motifs but also adjacency relations. The super-n-motifs model computes a vector representation of secondary structures as linear combinations of these motifs.We demonstrate the accuracy of our model for comparison of secondary structures from linear and circular RNA while also considering pseudoknot and G4 motifs. We show that the super-n-motifs representation effectively captures the most important structural features of secondary structures, as compared to other representations such as ordered tree, arc-annotated and string representations. Finally, we demonstrate the time efficiency of our model, which is alignment free and capable of performing large-scale comparisons of 10 000 secondary structures with an efficiency up to 4 orders of magnitude faster than existing approaches.The super-n-motifs model was implemented in C ++. Source code and Linux binary are freely available at http://jpsglouzon.github.io/supernmotifs/ .Shengrui.Wang@Usherbrooke.ca.Supplementary data are available at Bioinformatics o nline.
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