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相关论文: Combinatorics of locally optimal RNA secondary str…

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It is a classical result of Stein and Waterman that the asymptotic number of RNA secondary structures is $1.104366 n^{-3/2} 2.618034^n$. In this paper, we study combinatorial asymptotics for two special subclasses of RNA secondary…

定量方法 · 定量生物学 2013-06-19 Peter Clote , Evangelos Kranakis , Danny Krizanc , Bruno Salvy

We present a numerical study of the ultrametric properties of the set of RNA secondary structures with the maximum number of base pairs (energetically degenerate minima) within the maximum matching model (Nussinov algorithm). Using 18…

无序系统与神经网络 · 物理学 2026-05-27 A. P. Zubarev

We consider the Combinatorial RNA Design problem, a minimal instance of RNA design where one must produce an RNA sequence that adopts a given secondary structure as its minimal free-energy structure. We consider two free-energy models where…

定量方法 · 定量生物学 2016-08-05 Jozef Haleš , Alice Héliou , Ján Maňuch , Yann Ponty , Ladislav Stacho

A quantitative characterization of the relationship between molecular sequence and structure is essential to improve our understanding of how function emerges. This particular genotype-phenotype map has been often studied in the context of…

种群与进化 · 定量生物学 2017-04-20 José A. Cuesta , Susanna Manrubia

Combinatorial analysis of a certain abstract of RNA structures has been studied to investigate their statistics. Our approach regards the backbone of secondary structures as an alternate sequence of paired and unpaired sets of nucleotides,…

定量方法 · 定量生物学 2020-03-10 Sang Kwan Choi , Chaiho Rim , Hwajin Um

Background: In the Nearest-Neighbor Thermodynamic Model, a standard approach for RNA secondary structure prediction, the energy of the multiloops is modeled using a linear entropic penalty governed by three branching parameters. Although…

生物大分子 · 定量生物学 2025-10-15 Svetlana Poznanović , Owen Cardwell , Christine Heitsch

An RNA sequence is a word over an alphabet on four elements $\{A,C,G,U\}$ called bases. RNA sequences fold into secondary structures where some bases match one another while others remain unpaired. Pseudoknot-free secondary structures can…

数据结构与算法 · 计算机科学 2018-03-28 Édouard Bonnet , Paweł Rzążewski , Florian Sikora

We describe a dynamic programming algorithm for predicting optimal RNA secondary structure, including pseudoknots. The algorithm has a worst case complexity of ${\cal O}(N^6)$ in time and ${\cal O}(N^4)$ in storage. The description of the…

生物物理 · 物理学 2009-09-25 Elena Rivas , Sean R. Eddy

In this work, we consider the Combinatorial RNA Design problem, a minimal instance of the RNA design problem which aims at finding a sequence that admits a given target as its unique base pair maximizing structure. We provide complete…

定量方法 · 定量生物学 2015-06-22 Jozef Haleš , Ján Maňuch , Yann Ponty , Ladislav Stacho

Given an RNA sequence a, consider the network G = (V;E), where the set V of nodes consists of all secondary structures of a, and whose edge set E consists of all edges connecting two secondary structures whose base pair distance is 1.…

生物大分子 · 定量生物学 2016-10-31 Peter Clote

We show the expected order of RNA saturated secondary structures of size $n$ is $\log_4n(1+O(\frac{\log_2n}{n}))$, if we select the saturated secondary structure uniformly at random. Furthermore, the order of saturated secondary structures…

组合数学 · 数学 2011-07-18 Emma Yu Jin , Markus E. Nebel

In this paper we present the asymptotic enumeration of RNA structures with pseudoknots. We develop a general framework for the computation of exponential growth rate and the sub exponential factors for $k$-noncrossing RNA structures. Our…

生物大分子 · 定量生物学 2009-09-29 Emma Y. Jin , Christian M. Reidys

The primary structure of a ribonucleic acid (RNA) molecule can be represented as a sequence of nucleotides (bases) over the alphabet {A, C, G, U}. The secondary or tertiary structure of an RNA is a set of base pairs which form bonds between…

数据结构与算法 · 计算机科学 2015-01-05 Shihyen Chen , Zhuozhi Wang , Kaizhong Zhang

In biology, predicting RNA secondary structures plays a vital role in determining its physical and chemical properties. Although we have powerful energy models to predict them as well as parametric analysis to understand the models…

生物大分子 · 定量生物学 2023-05-01 Doan Dai Nguyen

Enumerative studies of RNA secondary structures were initiated four decades ago by Waterman and his coworkers. Since then, RNA secondary structures have been explored according to many different structural characteristics, for instance,…

组合数学 · 数学 2024-07-10 Ricky X. F. Chen , Christian M. Reidys , Michael S. Waterman

A growing number of RNA sequences are now known to have distributions of multiple stable sequences. Recent algorithms use the list of nucleotides in a sequence and auxiliary experimental data to predict such distributions. Although the…

组合数学 · 数学 2020-09-14 Torin Greenwood , Christine E. Heitsch

In this paper, we study the combinatorial set of RNA secondary structures of length $n$ with $m$ base-pairs. For a compact representation, we encode an RNA secondary structure by the corresponding Motzkin word. For this combinatorial set,…

数据结构与算法 · 计算机科学 2023-01-30 Yuriy Shablya , Dmitry Kruchinin

The contact map of a protein fold is a graph that represents the patterns of contacts in the fold. It is known that the contact map can be decomposed into stacks and queues. RNA secondary structures are special stacks in which the degree of…

组合数学 · 数学 2014-06-05 William Y. C. Chen , Qiang-Hui Guo , Lisa H. Sun , Jian Wang

In this paper we enumerate $k$-noncrossing RNA pseudoknot structures with given minimum stack-length. We show that the numbers of $k$-noncrossing structures without isolated base pairs are significantly smaller than the number of all…

生物大分子 · 定量生物学 2007-12-04 Emma Y. Jin , Christian M. Reidys

Models for RNA secondary structures (the topology of folded RNA) without pseudo knots are disordered systems with a complex state-space below a critical temperature. Hence, a complex dynamical (glassy) behavior can be expected, when…

无序系统与神经网络 · 物理学 2008-02-02 S. Wolfsheimer , B. Burghardt , A. Mann , A. K. Hartmann
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