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Software systems are composed of many interacting elements. A natural way to abstract over software systems is to model them as graphs. In this paper we consider software dependency graphs of object-oriented software and we study one…

Software Engineering · Computer Science 2017-04-11 Vincenzo Musco , Martin Monperrus , Philippe Preux

In this paper, we study a bipartite analogue of the `random graphs evolving by degrees' process. We are given a bipartitioned set of vertices $V$ into two disjoint parts ${L}$ and ${R}$ and possibly unequal positive constants $\alpha$ and…

Probability · Mathematics 2025-09-30 Neeladri Maitra

The modeling of time series is becoming increasingly critical in a wide variety of applications. Overall, data evolves by following different patterns, which are generally caused by different user behaviors. Given a time series, we define…

Machine Learning · Computer Science 2022-07-13 Wenjie Hu , Jianping Huang , Liang Wu , Yang Yang , Zongtao Liu , Zhanlin Sun , Bingshen Yao , Ke Chen

The purpose of this article is to introduce a new iterative algorithm with properties resembling real life bipartite graphs. The algorithm enables us to generate wide range of random bigraphs, which features are determined by a set of…

Artificial Intelligence · Computer Science 2010-11-03 Szymon Chojnacki , Mieczysław Kłopotek

Epidemics on complex networks is a widely investigated topic in the last few years, mainly due to the last pandemic events. Usually, real contact networks are dynamic, hence much effort has been invested in studying epidemics on evolving…

Physics and Society · Physics 2022-05-18 Hillel Sanhedrai , Shlomo Havlin

We investigate the evolution rules and degree distribution properties of the Software Heritage dataset, a large-scale growing network linking software source-code versions from open-source communities. The network spans more than 40 years…

Data Analysis, Statistics and Probability · Physics 2026-01-29 Guillaume Rousseau

In this work, we develop a stochastic model of gene gain and loss with the aim of inferring when (if at all) in evolutionary history and association between two genes arises. The data we consider is a species tree along with information on…

Populations and Evolution · Quantitative Biology 2023-09-07 Jiahao Diao , Malgorzata M. O'Reilly , Barbara R. Holland

The structure of molecular networks derives from dynamical processes on evolutionary time scales. For protein interaction networks, global statistical features of their structure can now be inferred consistently from several…

Statistical Mechanics · Physics 2007-05-23 Johannes Berg , Michael Lässig , Andreas Wagner

The distributed genome hypothesis states that the set of genes in a population of bacteria is distributed over all individuals that belong to the specific taxon. It implies that certain genes can be gained and lost from generation to…

Probability · Mathematics 2010-11-08 F. Baumdicker , W. R. Hess , P. Pfaffelhuber

Preferential attachment is often suggested to be the underlying mechanism of the growth of a network, largely due to that many real networks are, to a certain extent, scale-free. However, such attribution is usually made under debatable…

Applications · Statistics 2025-09-16 Clement Lee

We investigate a model of evolving random network, introduced by us previously {[}{\it Phys. Rev. Lett.} {\bf 83}, 5587 (1999){]} . The model is a generalization of the Bak-Sneppen model of biological evolution, with the modification that…

Statistical Mechanics · Physics 2009-10-31 Frantisek Slanina , Miroslav Kotrla

A network as a substrate for dynamic processes may have its own dynamics. We propose a model for networks which evolve together with diffusing particles through a coupled dynamics, and investigate emerging structural property. The model…

Statistical Mechanics · Physics 2009-11-10 Sang-Woo Kim , Jae Dong Noh

Diffusion and flow matching approaches to generative modeling have shown promise in domains where the state space is continuous, such as image generation or protein folding & design, and discrete, exemplified by diffusion large language…

The co-authorship network of scientists represents a prototype of complex evolving networks. By mapping the electronic database containing all relevant journals in mathematics and neuro-science for an eight-year period (1991-98), we infer…

Soft Condensed Matter · Physics 2009-11-07 A. L. Barabasi , H. Jeong , Z. Neda , E. Ravasz , A. Schubert , T. Vicsek

Graph neural networks (GNNs), which propagate the node features through the edges and learn how to transform the aggregated features under label supervision, have achieved great success in supervised feature extraction for both node-level…

Machine Learning · Statistics 2022-11-01 Yilin He , Chaojie Wang , Hao Zhang , Bo Chen , Mingyuan Zhou

Motivated by observations in sequence data of herpesviruses, we introduce a multi-locus model for the joint evolution of different genotypes in a virus population that is distributed across a population of hosts. In the model, virus…

Populations and Evolution · Quantitative Biology 2025-09-24 Raphael Eichhorn , Cornelia Pokalyuk

The rate equations are used to study the scale-free behavior of the weight distribution in evolving networks whose topology is determined only by degrees of preexisting vertices. An analysis of these equations shows that the degree…

Disordered Systems and Neural Networks · Physics 2007-05-23 W. Jezewski

Evolutionary dynamics is often viewed as a subtle process of change accumulation that causes a divergence among organisms and their genomes. However, this interpretation is an inheritance of a gradualistic view that has been challenged at…

Populations and Evolution · Quantitative Biology 2018-07-27 Jacobo Aguirre , Pablo Catalán , José A. Cuesta , Susanna Manrubia

Rapidly evolving viruses use antigenic drift as a key mechanism to evade host immunity and persist in real populations. While traditional models of antigenic drift and epidemic spread rely on low-dimensional antigenic spaces, genomic…

Populations and Evolution · Quantitative Biology 2025-06-05 Santiago Lamata-Otín , Octavian C. Rotita-Ion , Alex Arenas , David Soriano-Paños , Jesús Gómez-Gardeñes

Gene expression is significantly stochastic making modeling of genetic networks challenging. We present an approximation that allows the calculation of not only the mean and variance but also the distribution of protein numbers. We assume…

Molecular Networks · Quantitative Biology 2008-12-18 Vahid Shahrezaei , Peter S. Swain
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