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Related papers: Long-Time Mean Square Displacements in Proteins

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Recent years have seen a surge in methods for two-sample testing, among which the Maximum Mean Discrepancy (MMD) test has emerged as an effective tool for handling complex and high-dimensional data. Despite its success and widespread…

Machine Learning · Statistics 2026-05-21 Ikjun Choi , Ilmun Kim

Correlation length exponent $\nu$ for long linear DNA molecules was determined by direct measurement of the average end-to-end distance as a function of the contour length $s$ by means of atomic force microscopy (AFM). Linear DNA, up to…

Soft Condensed Matter · Physics 2009-11-11 Francesco Valle , Melanie Favre , Paolo De Los Rios , Angelo Rosa , Giovanni Dietler

We prove that for a one-dimensional infinite lattice, with long-range coupling among sites, the diffusion of an initial delta-like pulse in the bulk, is ballistic at all times. We obtain a closed-form expression for the mean square…

Disordered Systems and Neural Networks · Physics 2015-06-03 Alejandro J. Martinez , Mario I. Molina

A long-standing challenge encountered in modeling plasma dynamics is achieving practical Vlasov equation simulation in multiple spatial dimensions over large length and time scales. While direct multi-dimension Vlasov simulation methods…

Plasma Physics · Physics 2015-05-30 Harvey A. Rose , William Daughton

While it is very common to model diffusion as a random walk by assuming memorylessness of the trajectory and diffusive step lengths, these assumptions can lead to significant errors. This paper describes the extent to which a physical…

Statistical Mechanics · Physics 2025-08-07 Ludovico Cademartiri

Rigid bodies, made of smaller composite beads, are commonly used to simulate anisotropic particles with molecular dynamics or Monte Carlo methods. To accurately represent the particle shape and to obtain smooth and realistic effective pair…

Soft Condensed Matter · Physics 2024-02-20 B. Rusen Argun , Yu Fu , Antonia Statt

The non-Gaussian normal diffusion, i.e., the probability distribution function (PDF) is non-Gaussian but the mean squared displacement (MSD) depends on time linearly, has been observed in particle motions. Here we show by numerical…

Disordered Systems and Neural Networks · Physics 2016-04-06 Jianjin Wang , Yong Zhang , Hong Zhao

We report the melting temperature of free-standing silicene by carrying out molecular dynamics (MD) simulation experiments using optimzed Stillinger-Weber (SW) potential by Zhang {\it et al.}. The melting scenario of a free-standing…

Materials Science · Physics 2018-06-27 Tjun Kit Min , Tiem Leong Yoon , Thong Leng Lim

There is no agreement in the literature on the rate of diffusion of a particle in a cooling granular gas. Predictions and model assumptions range from the conventional to very exotic dependence of the mean square distance (MSD) on time.…

Statistical Mechanics · Physics 2021-11-12 Raphael Blumenfeld

We consider the problem of subspace estimation in a Bayesian setting. Since we are operating in the Grassmann manifold, the usual approach which consists of minimizing the mean square error (MSE) between the true subspace $U$ and its…

Methodology · Statistics 2015-05-27 Olivier Besson , Nicolas Dobigeon , Jean-Yves Tourneret

Approximation of entropies of various types using machine learning (ML) regression methods are shown for the first time. The ML models presented in this study define the complexity of the short time series by approximating dissimilar…

Machine Learning · Computer Science 2022-11-30 Andrei Velichko , Maksim Belyaev , Matthias P. Wagner , Alireza Taravat

Protein folding produces characteristic and functional three-dimensional structures from unfolded polypeptides or disordered coils. The emergence of extraordinary complexity in the protein folding process poses astonishing challenges to…

Biomolecules · Quantitative Biology 2013-08-14 Kelin Xia , Guo-Wei Wei

In this paper we propose a novel theoretical framework for interpreting long-range dynamical correlations unveiled in proteins through NMR measurements. The theoretical rationale relies on the hypothesis that correlated motions in proteins…

Biomolecules · Quantitative Biology 2014-04-03 Francesco Piazza

Turbulent thermal convection governs heat transport in systems ranging from stellar interiors to industrial heat exchangers. Two-dimensional Rayleigh-B\'enard convection serves as a paradigm for these flows, reproducing key features such as…

Protein footprinting is a new methodology that is based on probing, typically with the use of mass spectrometry, of reactivity of different aminoacid residues to a modifying reagent. Data thus obtained allow one to make inferences about…

Molecular Networks · Quantitative Biology 2010-12-21 Pasquale Moio , Arman Kulyyassov , Damien Vertut , Luc Camoin , Erlan Ramankulov , Marc Lipinski , Vasily Ogryzko

We present a new method for sampling stochastic displacements in Brownian Dynamics (BD) simulations of colloidal scale particles. The method relies on a new formulation for Ewald summation of the Rotne-Prager-Yamakawa (RPY) tensor, which…

Soft Condensed Matter · Physics 2017-04-26 A. M. Fiore , F. Balboa Usabiaga , A. Donev , J. W. Swan

Intrachain contact formation rates, fundamental to the dynamics of biopolymer self-organization such as protein folding, can be monitored in the laboratory through fluorescence quenching measurements. The common approximations for the…

Condensed Matter · Physics 2009-11-07 John J. Portman

Anomalous diffusion is frequently described by scaled Brownian motion (SBM), a Gaussian process with a power-law time dependent diffusion coefficient. Its mean squared displacement is $\langle x^2(t)\rangle\simeq\mathscr{K}(t)t$ with…

Statistical Mechanics · Physics 2014-12-24 J. -H. Jeon , A. V. Chechkin , R. Metzler

Single-file diffusion (SFD) of an infinite one-dimensional chain of interacting particles has a long-time mean-square displacement (MSD) ~t^1/2, independent of the type of inter-particle repulsive interaction. This behavior is also observed…

Statistical Mechanics · Physics 2010-11-19 D. V. Tkachenko , V. R. Misko , F. M. Peeters

Various studies that address the compressed sensing problem with Multiple Measurement Vectors (MMVs) have been recently carried. These studies assume the vectors of the different channels to be jointly sparse. In this paper, we relax this…

Machine Learning · Computer Science 2016-11-14 Hamid Palangi , Rabab Ward , Li Deng