15 papers · ranked by Valyu relevance
Junya Wang, Yi-Jiao Zhang, Cong Xu, Jiaze Li + 5 more
The evolution processes of complex systems carry key information in the systems’ functional properties. Applying machine learning algorithms, we demonstrate that the historical formation process of various networked complex systems can be extracted, including protein-protein interaction, ecology, and social network…
Dongqi Fu, Jingrui He
Graph structures have attracted much research attention for carrying complex relational information. Based on graphs, many algorithms and tools are proposed and developed for dealing with real-world tasks such as recommendation, fraud detection, molecule design, etc. In this paper, we first discuss three topics of…
Kateryna Melnyk, Kuba Weimann, Tim O. F. Conrad
Large-scale perturbations in the microbiome constitution are strongly correlated, whether as a driver or a consequence, with the health and functioning of human physiology. However, understanding the difference in the microbiome profiles of healthy and ill individuals can be complicated due to the large number of…
Yang Ping Kuo, Oana Carja, Christian Hilbe
To design population topologies that can accelerate rates of solution discovery in directed evolution problems or for evolutionary optimization applications, we must first systematically understand how population structure shapes evolutionary outcome. Using the mathematical formalism of evolutionary graph theory…
Badhan Das, Lenwood S. Heath, Anna Bernasconi
The SARS-CoV-2 virus has undergone extensive mutations over time, resulting in considerable genetic diversity among circulating strains. This diversity directly affects important viral characteristics, such as transmissibility and disease severity. During a viral outbreak, the rapid mutation rate produces a large cloud…
Gowthami Vusirikkayala, V. Madhu Viswanatham
Dynamic community detection is an increasingly important research topic in network science. In real-world networks, edges and nodes change over time; therefore, the community structure must evolve. Due to the dynamic nature of networks, many community detection algorithms rely on static graph assumptions and may not…
Yucai Jiang, Rongying Shan, Gang Fu, Zhuolin Li + 4 more
Graph neural networks (GNNs), which learn node representations via aggregating their neighbors, have shown superior performance and become the de facto efficient toolkit for analyzing and learning from data with structured properties. However, most existing GNNs are designed for static graphs and assume fixed graph…
Jianrun Shi, Leiyang Cui, Bo Gu, Bin Lyu + 2 more
'Leopoldo Angrisani'] Mobile traffic prediction enables the efficient utilization of network resources and enhances user experience. In this paper, we propose a state transition graph-based spatial-temporal attention network (STG-STAN) for cell-level mobile traffic prediction, which is designed to exploit the…
Nikhil Sharma, Suman G. Das, Joachim Krug, Arne Traulsen
Birth-death models are used to understand the interplay of genetic drift and natural selection. While well-mixed populations remain unaffected by the order of birth and death and where selection acts, evolutionary outcomes in spatially structured populations are affected by these choices. We show that the choice of…
Belgin Ergenç Bostanoğlu, Nourhan Abuzayed, Bilal Alatas
Frequent subgraph mining (FSM) is an essential and challenging graph mining task used in several applications of the modern data science. Some of the FSM algorithms have the objective of finding all frequent subgraphs whereas some of the algorithms focus on discovering frequent subgraphs approximately. On the other…
Alia Abbara, Lisa Pagani, Celia García-Pareja, Anne-Florence Bitbol + 1 more
'Chaitanya S Gokhale'] In nature, most microbial populations have complex spatial structures that can affect their evolution. Evolutionary graph theory predicts that some spatial structures modelled by placing individuals on the nodes of a graph affect the probability that a mutant will fix. Evolution experiments are…
Sedigheh Yagoobi, Nikhil Sharma, Arne Traulsen
The structure of a population strongly influences its evolutionary dynamics. In various settings ranging from biology to social systems, individuals tend to interact more often with those present in their proximity and rarely with those far away. A common approach to model the structure of a population is evolutionary…
Yang Ping Kuo, César Nombela-Arrieta, Oana Carja
How the spatial arrangement of a population shapes its evolutionary dynamics has been of long-standing interest in population genetics. Most previous studies assume a small number of demes or symmetrical structures that, most often, act as well-mixed populations. Other studies use network theory to study more…
David A Brewster, Jakub Svoboda, Dylan Roscow, Krishnendu Chatterjee + 3 more
'Josef Tkadlec' 'Martin A Nowak' 'Sergey Gavrilets'] Title: Abstract We examine population structures for their ability to maintain diversity in neutral evolution. We use the general framework of evolutionary graph theory and consider birth-death (bd) and death-birth (db) updating. The population is of size N.…
Victor Boussange, Loïc Pellissier
Differentiation mechanisms are influenced by the properties of the landscape over which individuals interact, disperse and evolve. Here, we investigate how habitat connectivity and habitat heterogeneity affect phenotypic differentiation by formulating a stochastic eco-evolutionary model where individuals are structured…