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Understanding the base pairing of an RNA sequence provides insight into its molecular structure.By mining suboptimal sampling data, RNAprofiling 1.0 identifies the dominant helices in low-energy secondary structures as features, organizes…

Biomolecules · Quantitative Biology 2023-03-29 Forrest Hurley , Christine Heitsch

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…

Populations and Evolution · Quantitative Biology 2017-04-20 José A. Cuesta , Susanna Manrubia

RNA secondary structure is an important computational model to understand how genetic variation maps into phenotypic (structural) variation. Evolutionary innovation in RNA structures is facilitated by neutral networks, large connected sets…

Populations and Evolution · Quantitative Biology 2008-01-22 Sumedha , Olivier C Martin , Andreas Wagner

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…

Quantitative Methods · Quantitative Biology 2015-06-22 Jozef Haleš , Ján Maňuch , Yann Ponty , Ladislav Stacho

While artificial intelligence has made remarkable strides in revealing the relationship between biological macromolecules' primary sequence and tertiary structure, designing RNA sequences based on specified tertiary structures remains…

Biomolecules · Quantitative Biology 2024-03-08 Cheng Tan , Yijie Zhang , Zhangyang Gao , Bozhen Hu , Siyuan Li , Zicheng Liu , Stan Z. Li

Ab initio RNA secondary structure predictions have long dismissed helices interior to loops, so-called pseudoknots, despite their structural importance. Here, we report that many pseudoknots can be predicted through long time scales RNA…

Biological Physics · Physics 2009-11-10 A. Xayaphoummine , T. Bucher , F. Thalmann , H. Isambert

Many recent exciting discoveries have revealed the versatility of RNAs and their importance in a variety of cellular functions which are strongly coupled to RNA structures. To understand the functions of RNAs, some structure prediction…

Biological Physics · Physics 2014-08-29 Ya-Zhou Shi , Yuan-Yan Wu , Feng-Hua Wang , Zhi-Jie Tan

Given usefulness of protein language models (LMs) in structure and functional inference, RNA LMs have received increased attentions in the last few years. However, these RNA models are often not compared against the same standard. Here, we…

Biomolecules · Quantitative Biology 2025-05-15 He Wang , Yikun Zhang , Jie Chen , Jian Zhan , Yaoqi Zhou

RNA design shows growing applications in synthetic biology and therapeutics, driven by the crucial role of RNA in various biological processes. A fundamental challenge is to find functional RNA sequences that satisfy given structural…

Biomolecules · Quantitative Biology 2024-04-18 Han Huang , Ziqian Lin , Dongchen He , Liang Hong , Yu Li

RNA-RNA binding is an important phenomenon observed for many classes of non-coding RNAs and plays a crucial role in a number of regulatory processes. Recently several MFE folding algorithms for predicting the joint structure of two…

Combinatorics · Mathematics 2010-06-16 Thomas J. X. Li , Christian M. Reidys

The statistical mechanics of heteropolymer structure formation is studied in the context of RNA secondary structures. A designed RNA sequence biased energetically towards a particular native structure (a hairpin) is used to study the…

Statistical Mechanics · Physics 2009-10-31 R. Bundschuh , T. Hwa

We view the folding of RNA-sequences as a map that assigns a pattern of base pairings to each sequence, known as secondary structure. These preimages can be constructed as random graphs (i.e. the neutral networks associated to the structure…

adap-org · Physics 2008-02-03 Christian V. Forst , Christian Reidys , Jacqueline Weber

No existing algorithm can start with arbitrary RNA sequences and return the precise, three-dimensional structures that ensures their biological function. This chapter outlines current algorithms for automated RNA structure prediction…

Biomolecules · Quantitative Biology 2011-03-17 Kyle Beauchamp , Parin Sripakdeevong , Rhiju Das

This dissertation presents a multifaceted look into the structural decomposition of permutation classes. The theory of permutation patterns is a rich and varied field, and is a prime example of how an accessible and intuitive definition…

Combinatorics · Mathematics 2014-10-13 Cheyne Homberger

Extracting an understanding of the underlying system from high dimensional data is a growing problem in science. Discovering informative and meaningful features is crucial for clustering, classification, and low dimensional data embedding.…

Machine Learning · Statistics 2019-12-10 Samuel Melton , Sharad Ramanathan

Motivation: RNA design aims to find RNA sequences that fold into a given target secondary structure, a problem also known as RNA inverse folding. However, not all target structures are designable. Recent advances in RNA designability have…

Data Structures and Algorithms · Computer Science 2026-04-28 Tianshuo Zhou , David H. Mathews , Liang Huang

Background: RNA exhibits a variety of structural configurations. Here we consider a structure to be tantamount to the noncrossing Watson-Crick and \pairGU-base pairings (secondary structure) and additional cross-serial base pairs. These…

Combinatorics · Mathematics 2010-03-11 James Z. M. Gao , Linda Y. M. Li , Christian M. Reidys

Existing state-of-the-art methods that take a single RNA sequence and predict the corresponding RNA secondary-structure are thermodynamic methods. These predict the most stable RNA structure, but do not consider the process of structure…

Biomolecules · Quantitative Biology 2012-07-26 Jeff R. Proctor , Irmtraud M. Meyer

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…

Disordered Systems and Neural Networks · Physics 2008-02-02 S. Wolfsheimer , B. Burghardt , A. Mann , A. K. Hartmann

In the face of rapidly accumulating genomic data, our understanding of the RNA regulatory code remains incomplete. Recent self-supervised methods in other domains have demonstrated the ability to learn rules underlying the data-generating…

Machine Learning · Computer Science 2023-10-18 Philip Fradkin , Ruian Shi , Bo Wang , Brendan Frey , Leo J. Lee