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This paper aims at a comprehensive understanding on the novel elastic property of double-stranded DNA (dsDNA) discovered very recently through single-molecule manipulation techniques. A general elastic model for double-stranded biopolymers…

Soft Condensed Matter · Physics 2009-10-31 Haijun Zhou , Yang Zhang , Zhong-can Ou-Yang

We consider the evolution of a network of neurons, focusing on the asymptotic behavior of spikes dynamics instead of membrane potential dynamics. The spike response is not sought as a deterministic response in this context, but as a…

Data Analysis, Statistics and Probability · Physics 2010-08-27 J. C. Vasquez , B. Cessac , T. Viéville

The estimation of entropy rates for stationary discrete-valued stochastic processes is a well studied problem in information theory. However, estimating the entropy rate for stationary continuous-valued stochastic processes has not received…

Information Theory · Computer Science 2021-05-26 Andrew Feutrill , Matthew Roughan

Tethered particle experiments use light microscopy to measure the position of a micrometer-sized bead tethered to a microscope slide via a ~micrometer length polymer, in order to infer the behavior of the invisible polymer. Currently, this…

Biological Physics · Physics 2009-11-13 John F. Beausang , Chiara Zurla , Carlo Manzo , David Dunlap , Laura Finzi , Philip C. Nelson

A methodology for the statistical mechanical analysis of polymeric chains under tension introduced previously is extended to include torque. The response of individual bonds between monomers or of entire groups of monomers to a combination…

Soft Condensed Matter · Physics 2022-06-15 Aaron C. Meyer , Michael Karbach , Ping Lu , Gerhard Müller

The aim of this work is to provide a rigorous mathematical analysis of a stochastic concatenation model presented by Sobottka and Hart (2011) which allows approximation of the first-order stochastic structure in bacterial DNA by means of a…

Genomics · Quantitative Biology 2019-11-28 Andrew G. Hart , M. Sobottka

Foundation models in genomics have shown mixed success compared to their counterparts in natural language processing. Yet, the reasons for their limited effectiveness remain poorly understood. In this work, we investigate the role of…

Machine Learning · Computer Science 2026-04-07 Maxime Rochkoulets , Lovro Vrček , Mile Šikić

The entropy of a binary symmetric Hidden Markov Process is calculated as an expansion in the noise parameter epsilon. We map the problem onto a one-dimensional Ising model in a large field of random signs and calculate the expansion…

Information Theory · Computer Science 2009-11-11 O. Zuk , I. Kanter , E. Domany

This article proposes a novel approach to statistical alignment of nucleotide sequences by introducing a context dependent structure on the substitution process in the underlying evolutionary model. We propose to estimate alignments and…

Statistics Theory · Mathematics 2011-07-18 Ana Arribas-Gil , Catherine Matias

Signal processing (SP) techniques convert DNA and protein sequences into information that lead to successful drug discovery. One must, however, be aware about the difference between information and entropy1. Eight other physical properties…

Molecular Networks · Quantitative Biology 2007-05-23 Stan Bumble

We use statistical estimates of the entropy rate of spike train data in order to make inferences about the underlying structure of the spike train itself. We first examine a number of different parametric and nonparametric estimators (some…

Neurons and Cognition · Quantitative Biology 2008-03-27 Yun Gao , Ioannis Kontoyiannis , Elie Bienenstock

For a Markovian dynamics on discrete states, the logarithmic ratio of waiting-time distributions between two successive, instantaneous transitions in forward and backward direction is a measure of time-irreversibility. It thus serves as an…

Statistical Mechanics · Physics 2024-06-13 Ellen Meyberg , Julius Degünther , Udo Seifert

The entanglement entropy of a subsystem of a quantum system is expressed, in the replica approach, through analytic continuation with respect to n of the trace of the n-th power of the reduced density matrix. This trace can be thought of as…

High Energy Physics - Theory · Physics 2008-12-18 Michele Caraglio , Ferdinando Gliozzi

Link-prediction is an active research field within network theory, aiming at uncovering missing connections or predicting the emergence of future relationships from the observed network structure. This paper represents our contribution to…

Physics and Society · Physics 2018-07-20 Federica Parisi , Guido Caldarelli , Tiziano Squartini

Similarity-sensitive entropy measures the uncertainty of a probability law relative to a similarity kernel that encodes the distinguishability between states. We develop a measure-theoretic treatment covering both finite similarity matrices…

Probability · Mathematics 2026-05-29 Joseph Samuel Miller

We study the notion of approximate entropy within the framework of network theory. Approximate entropy is an uncertainty measure originally proposed in the context of dynamical systems and time series. We firstly define a purely structural…

Disordered Systems and Neural Networks · Physics 2013-05-30 James West , Lucas Lacasa , Simone Severini , Andrew Teschendorff

In this note, we studied the asymptotic behaviour of the length of the longest common substring for run-length encoded sequences. When the original sequences are generated by an $\alpha$-mixing process with exponential decay (or…

Probability · Mathematics 2020-12-14 Jerome Rousseau

This work derives a theoretical value for the entropy of a Linear Additive Markov Process (LAMP), an expressive model able to generate sequences with a given autocorrelation structure. While a first-order Markov Chain model generates new…

Information Theory · Computer Science 2023-01-10 Bridget Smart , Matthew Roughan , Lewis Mitchell

Entanglement entropies have revealed, in the last years, to be a powerful tool to extract information about the physics of condensed-matter systems. In the first part of this thesis, we show how to extract essential details about the…

Strongly Correlated Electrons · Physics 2013-09-17 Luca Taddia

The structure of the network can be described by motifs, which are subgraphs that often repeat themselves. In order to understand the structure of network motifs, it is of great importance to study subgraphs from the perspective of…

General Topology · Mathematics 2019-10-25 Ruize Gao , Ying Zhao