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We consider the folding of a self-avoiding homopolymer on a lattice, with saturating hydrogen bond interactions. Our goal is to numerically evaluate the statistical distribution of the topological genus of pseudoknotted configurations. The…

Biomolecules · Quantitative Biology 2009-11-11 G. Vernizzi , P. Ribeca , H. Orland , A. Zee

We use mesoscopic non-equilibrium thermodynamics theory to describe RNA unfolding under tension. The theory introduces reaction coordinates, characterizing a continuum of states for each bond in the molecule. The unfolding considered is so…

Statistical Mechanics · Physics 2007-09-18 J. M. Rubi , D. Bedeaux , S. Kjelstrup

While the structure of chromatin has been studied in great detail on length scales below 30 nm, amazingly little is known about the higher-order folding motifs of chromatin in interphase. Recent experiments give evidence that the folding…

Soft Condensed Matter · Physics 2009-02-16 Manfred Bohn , Dieter W. Heermann , Roel van Driel

Recent single-molecule pulling experiments have shown how it is possible to manipulate RNA molecules using optical tweezers force microscopy. We investigate a minimal model for the experimental setup which includes a RNA molecule connected…

Statistical Mechanics · Physics 2009-11-10 Maria Manosas , Felix Ritort

An underlying structure in several sampling-based methods for continuous multi-robot motion planning (MRMP) is the tensor roadmap (TR), which emerges from combining multiple PRM graphs constructed for the individual robots via a tensor…

Robotics · Computer Science 2023-02-13 Dror Dayan , Kiril Solovey , Marco Pavone , Dan Halperin

We assess the reliability of the recently developed approach denominated Dominant Reaction Pathways (DRP) by studying the folding of a 16-residue beta-hairpin, within a coarse-grained Go-type model. We show that the DRP predictions are in…

Biomolecules · Quantitative Biology 2008-06-24 Pietro Faccioli

The paper proposes to employ deep convolutional neural networks (CNNs) to classify noncoding RNA (ncRNA) sequences. To this end, we first propose an efficient approach to convert the RNA sequences into images characterizing their…

Computer Vision and Pattern Recognition · Computer Science 2020-08-25 Brian McClannahan , Krushi Patel , Usman Sajid , Cuncong Zhong , Guanghui Wang

In Hamiltonian systems subjected to periodic perturbations the stable and unstable manifolds of the unstable periodic orbits provide the dynamical "skeleton" that drives the mixing process and bounds the chaotic regions of the phase space.…

Plasma Physics · Physics 2016-10-05 David Ciro Taborda , Todd Edwin Evans , Iberê Luiz Caldas

A central goal of protein-folding theory is to predict the stochastic dynamics of transition paths --- the rare trajectories that transit between the folded and unfolded ensembles --- using only thermodynamic information, such as a…

Biomolecules · Quantitative Biology 2018-08-09 William M. Jacobs , Eugene I. Shakhnovich

The modeling of solid-state transformations, such as polymorphic transitions and chemical reactions in molecular crystals, is vital for many applications including drug design or the development of new synthesis methods. However, a…

Chemical Physics · Physics 2025-06-17 Natalia Goncharova , Johannes Hoja

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

Identifying phase transitions and classifying phases of matter is central to understanding the properties and behavior of a broad range of material systems. In recent years, machine-learning (ML) techniques have been successfully applied to…

Disordered Systems and Neural Networks · Physics 2023-06-23 Julian Arnold , Frank Schäfer

Single-cell trajectory analysis aims to reconstruct the biological developmental processes of cells as they evolve over time, leveraging temporal correlations in gene expression. During cellular development, gene expression patterns…

Applications · Statistics 2026-03-30 Junhao Zhu , Kevin Zhang , Zhaolei Zhang , Dehan Kong

Structural prediction has long been considered critical in RNA research, especially following the success of AlphaFold2 in protein studies, which has drawn significant attention to the field. While recent advances in machine learning and…

Biomolecules · Quantitative Biology 2024-09-26 Jiaxing Yang

Background. Dramatic increases in RNA structural data have made it possible to recognize its conformational preferences much better than a decade ago. This has created an opportunity to use discrete restraint-based conformational sampling…

Biomolecules · Quantitative Biology 2007-10-23 Swanand Gore , Tom Blundell

NaCl crystal nucleation from metastable solutions has long been considered to occur according to a single-step mechanism. Recent experimental observations suggest that NaCl crystals emerge from disordered intermediates which is seemingly at…

Materials Science · Physics 2022-10-12 Aaron R. Finney , Matteo Salvalaglio

Single molecule force spectroscopy methods can be used to generate folding trajectories of biopolymers from arbitrary regions of the folding landscape. We illustrate the complexity of the folding kinetics and generic aspects of the collapse…

Biological Physics · Physics 2015-05-14 Changbong Hyeon , Greg Morrison , David L. Pincus , D. Thirumalai

Understanding the mechanisms underlying crystal formation is crucial. For most systems, crystallization typically goes through a nucleation process that involves dynamics that happen at short time and length scales. Due to this, molecular…

Statistical Mechanics · Physics 2025-11-04 Steven W. Hall , Porhouy Minh , Sapna Sarupria

The biological functions of proteins often depend on dynamic structural ensembles. In this work, we develop a flow-based generative modeling approach for learning and sampling the conformational landscapes of proteins. We repurpose highly…

Biomolecules · Quantitative Biology 2024-09-04 Bowen Jing , Bonnie Berger , Tommi Jaakkola
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