English
Related papers

Related papers: Entropy concepts and DNA investigations

200 papers

The channel output entropy of a transmitted sequence is the entropy of the possible channel outputs and similarly the channel input entropy of a received sequence is the entropy of all possible transmitted sequences. The goal of this work…

Information Theory · Computer Science 2025-06-04 Shubhransh Singhvi , Omer Sabary , Daniella Bar-Lev , Eitan Yaakobi

We introduce distance entropy as a measure of homogeneity in the distribution of path lengths between a given node and its neighbours in a complex network. Distance entropy defines a new centrality measure whose properties are investigated…

Physics and Society · Physics 2018-05-09 Massimo Stella , Manlio De Domenico

Stochastic blockmodels are generative network models where the vertices are separated into discrete groups, and the probability of an edge existing between two vertices is determined solely by their group membership. In this paper, we…

Statistical Mechanics · Physics 2013-11-12 Tiago P. Peixoto

The field of complex networks studies a wide variety of interacting systems by representing them as networks. To understand their properties and mutual relations, the randomisation of network connections is a commonly used tool. However,…

Statistical Mechanics · Physics 2024-10-18 Noam Abadi , Franco Ruzzenenti

Complexity metrics and machine learning (ML) models have been utilized to analyze the lengths of segmental genomic entities like: exons, introns, intergenic and repeat/unique DNA sequences, in each of the 22 human chromosomes. The purpose…

Eukaryote genomes contain excessively introns, inter-genic and other non-genic sequences that appear to have no vital functional role or phenotype manifestation. Their existence, a long-standing puzzle, is viewed from the principle of…

Populations and Evolution · Quantitative Biology 2008-07-08 Salla Jaakkola , Sedeer El-Showk , Arto Annila

In a genetic algorithm, fluctuations of the entropy of a genome over time are interpreted as fluctuations of the information that the genome's organism is storing about its environment, being this reflected in more complex organisms. The…

Computational Engineering, Finance, and Science · Computer Science 2010-11-04 Manuel Cebrian , Manuel Alfonseca , Alfonso Ortega

Proteins are essential components of living systems, capable of performing a huge variety of tasks at the molecular level, such as recognition, signalling, copy, transport, ... The protein sequences realizing a given function may largely…

Biomolecules · Quantitative Biology 2016-02-17 John Barton , Arup Chakraborty , Simona Cocco , Hugo Jacquin , Rémi Monasson

We consider in this paper the problem of computing the entropy of a braid. We recall its definition and construct, for each braid, a sequence of real numbers, whose limit is its entropy. We state one conjecture about the convergence speed,…

Dynamical Systems · Mathematics 2009-09-29 Jacques-Olivier Moussafir

Permutation entropy quantifies the diversity of possible orderings of the values a random or deterministic system can take, as Shannon entropy quantifies the diversity of values. We show that the metric and permutation entropy…

Chaotic Dynamics · Physics 2016-08-16 Jose M. Amigo , Matthew B. Kennel , Ljupco Kocarev

The elasticity of DNA catenanes, i.e. multiply linked DNA rings, is investigated using the Gauss invariant as a minimal model for topology conservation. An effective elastic free energy as a function of the distance $R$ between segments…

Soft Condensed Matter · Physics 2007-05-23 M. Otto , T. A. Vilgis

The concept of entropy rate for a dynamical process on a graph is introduced. We study diffusion processes where the node degrees are used as a local information by the random walkers. We describe analitically and numerically how the degree…

Statistical Mechanics · Physics 2009-11-13 Jesus Gomez-Gardenes , Vito Latora

Boolean network models of strongly connected modules are capable of capturing the high regulatory complexity of many biological gene regulatory circuits. We study numerically the previously introduced basin entropy, a parameter for the…

Disordered Systems and Neural Networks · Physics 2009-11-13 P. Krawitz , I. Shmulevich

We introduce a complexity measure for symbolic sequences. Starting from a segmentation procedure of the sequence, we define its complexity as the entropy of the distribution of lengths of the domains of relatively uniform composition in…

Classical Physics · Physics 2007-05-23 Ana P. Majtey , Ramon Roman-Roldan , Pedro W. Lamberti

Random walks have been intensively studied on regular and complex networks, which are used to represent pairwise interactions. Nonetheless, recent works have demonstrated that many real-world processes are better captured by higher-order…

Physics and Society · Physics 2023-06-19 Pietro Traversa , Guilherme Ferraz de Arruda , Yamir Moreno

Biological sequences do not come at random. Instead, they appear with particular frequencies that reflect properties of the associated system or phenomenon. Knowing how biological sequences are distributed in sequence space is thus a…

Biological Physics · Physics 2024-04-18 Wei-Chia Chen , Juannan Zhou , David M. McCandlish

Various approaches to alignment-free sequence comparison are based on the length of exact or inexact word matches between two input sequences. Haubold {\em et al.} (2009) showed how the average number of substitutions between two DNA…

Populations and Evolution · Quantitative Biology 2017-09-06 Burkhard Morgenstern , Svenja Schöbel , Chris-André Leimeister

This is a preliminary article stating and proving a new maximum entropy theorem. The entropies that we consider can be used as measures of biodiversity. In that context, the question is: for a given collection of species, which frequency…

Information Theory · Computer Science 2011-01-14 Tom Leinster

Models of networks play a major role in explaining and reproducing empirically observed patterns. Suitable models can be used to randomize an observed network while preserving some of its features, or to generate synthetic graphs whose…

Neural networks have dramatically increased our capacity to learn from large, high-dimensional datasets across innumerable disciplines. However, their decisions are not easily interpretable, their computational costs are high, and building…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Mackenzie J. Meni , Ryan T. White , Michael Mayo , Kevin Pilkiewicz