计数可辨别的RNA二级结构。

IF 1.4 4区 生物学 Q4 BIOCHEMICAL RESEARCH METHODS Journal of Computational Biology Pub Date : 2023-10-01 Epub Date: 2023-10-09 DOI:10.1089/cmb.2022.0501
Masaru Nakajima, Andrew D Smith
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引用次数: 0

摘要

RNA二级结构是理解这些大分子空间折叠行为的重要抽象概念。许多二次结构算法涉及一个通用的动态规划设置,以利用二次结构可以分解为子结构的特性。Dirks等人指出,这种设置不能直接解决二级结构之间的可区分性问题,这是在允许非平凡对称的序列类中出现的。循环序列就是其中之一。我们研究了可区分二级结构的计数问题。根据群论的基本结果,我们确定了二级结构的有用子集。然后,我们扩展了Hofacker等人的算法,用于计算这些子集的大小。这产生了一种三次时间算法来计算与给定圆形序列兼容的可区分结构。此外,这种通用方法可用于解决感兴趣的RNA结构涉及对称性的类似问题。
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Counting Distinguishable RNA Secondary Structures.

RNA secondary structures are essential abstractions for understanding spacial folding behaviors of those macromolecules. Many secondary structure algorithms involve a common dynamic programming setup to exploit the property that secondary structures can be decomposed into substructures. Dirks et al. noted that this setup cannot directly address an issue of distinguishability among secondary structures, which arises for classes of sequences that admit nontrivial symmetry. Circular sequences are among these. We examine the problem of counting distinguishable secondary structures. Drawing from elementary results in group theory, we identify useful subsets of secondary structures. We then extend an algorithm due to Hofacker et al. for computing the sizes of these subsets. This yields a cubic-time algorithm to count distinguishable structures compatible with a given circular sequence. Furthermore, this general approach may be used to solve similar problems for which the RNA structures of interest involve symmetries.

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来源期刊
Journal of Computational Biology
Journal of Computational Biology 生物-计算机:跨学科应用
CiteScore
3.60
自引率
5.90%
发文量
113
审稿时长
6-12 weeks
期刊介绍: Journal of Computational Biology is the leading peer-reviewed journal in computational biology and bioinformatics, publishing in-depth statistical, mathematical, and computational analysis of methods, as well as their practical impact. Available only online, this is an essential journal for scientists and students who want to keep abreast of developments in bioinformatics. Journal of Computational Biology coverage includes: -Genomics -Mathematical modeling and simulation -Distributed and parallel biological computing -Designing biological databases -Pattern matching and pattern detection -Linking disparate databases and data -New tools for computational biology -Relational and object-oriented database technology for bioinformatics -Biological expert system design and use -Reasoning by analogy, hypothesis formation, and testing by machine -Management of biological databases
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