Article
Neurosciences
Melanie A. Matyi, Sebastian M. Cioaba, Marie T. Banich, Jeffrey M. Spielberg
Summary: Effective amygdalar functionality relies on a complex network of interconnected brain regions. Novel graph theory methods were applied to identify key nodes supporting amygdalar interactions with the larger brain network. Different aspects of amygdalar communication were found to be associated with separable sets of regions, expanding the understanding of amygdala function.
Article
Neurosciences
Ningning Zeng, Andre Aleman, Chong Liao, Huihua Fang, Pengfei Xu, Yuejia Luo
Summary: This study examined the intrinsic brain networks in healthy individuals with different levels of apathy. The results showed that individuals with high apathy had lower average participation coefficient in the subcortical network, particularly in the amygdala. Importantly, weaker effective connectivity was observed from the hippocampus and parahippocampal gyrus to the amygdala, and from the amygdala to the parahippocampal gyrus and medial frontal cortex in individuals with apathy. These findings suggest aberrant communication within the cortical-to-subcortical network in individuals with high apathy. This study sheds light on the neural basis of apathy in subclinical populations.
Article
Behavioral Sciences
Tessa F. Blanken, Joe Bathelt, Marie K. Deserno, Lily Voge, Denny Borsboom, Linda Douw
Summary: In recent years, applications of network science have increased in various fields, but there has been a lack of collaboration between clinical neuroscience and psychopathology. The promise of integrating these network applications lies in a united framework to address the link between brain and behavior. This paper introduces conventions in both fields, highlights similarities, and creates a common language to pave the way for further development of multi-modal networks and integration of brain and behavior.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
(2021)
Article
Mathematics
Yelai Feng, Huaixi Wang, Chao Chang, Hongyi Lu
Summary: Betweenness centrality is an important index in complex network analysis for evaluating the importance of nodes and edges. Existing algorithms fail to show the change of betweenness centrality with path growth, while our proposed new algorithm calculates betweenness centrality hierarchically and accelerates computation using GPUs. Based on the new algorithm, we discover an intrinsic correlation between the distribution of the shortest paths and betweenness centrality. Additionally, we find that some nodes with a betweenness centrality index of 0 still have critical significance in real networks.
Article
Mathematics, Interdisciplinary Applications
S. E. Schaeffer, V. Valdes, J. Figols, I Bachmann, F. Morales, J. Bustos-Jimenez
Summary: In this paper, recent proposals aiming to quantify the resilience and robustness of a graph in numerical terms are briefly surveyed, with characterizations from journal articles published in the last two decades catalogued. The various applications of these characterizations are then described. Through experimentation with implementations on several graph-generation models, open problems and future directions are analyzed in the conclusion.
JOURNAL OF COMPLEX NETWORKS
(2021)
Article
Computer Science, Information Systems
Moonsu Jang, Donghyun Kim, Daehee Seo, Yongmin Ju, Seungho Ryu, Hyunsoo Yoon
Summary: The recent surge in cyber attacks has led to the necessity of regular massive Cyber Defense eXercises for employees. The newest CDX platform utilizes edge computing to manage costs for blue team members in real time. However, the challenge lies in the shortage of red team members with expertise in cyber offense.
COMPUTER COMMUNICATIONS
(2021)
Article
Automation & Control Systems
Ekaterina Dudkina, Michelangelo Bin, Jane Breen, Emanuele Crisostomi, Pietro Ferraro, Steve Kirkland, Jakub Marecek, Roderick Murray-Smith, Thomas Parisini, Lewi Stone, Serife Yilmaz, Robert Shorten
Summary: This paper reviews classic methods for node ranking and compares their performance in a benchmark network that considers the community-based structure of society. The outcome of the ranking procedure is then used to decide which individuals should be tested, and possibly quarantined, first. Finally, the extension of these ranking methods to weighted graphs is explored, and the importance of weights in a contact network is investigated through a toy model and comparison of node rankings in the context of disease spread.
INTERNATIONAL JOURNAL OF CONTROL
(2023)
Article
Computer Science, Information Systems
Yuede Ma, Matthias Dehmer, Urs-Martin Kunzi, Abbe Mowshowitz, Shailesh Tripathi, Modjtaba Ghorbani, Frank Emmert-Streib
Summary: This paper compares two measures of graph symmetry based on the number and sizes of vertex orbits of the automorphism group, using a real valued distance measure to establish the limiting value of distances for several well-known classes of graphs.
INFORMATION SCIENCES
(2021)
Review
Automation & Control Systems
Resul Das, Mucahit Soylu
Summary: This comprehensive review provides an in-depth analysis of the role of graph theory and graph visualization in scientific studies. It explores different graph types, special graphs, and the challenges and advancements in graph visualization techniques. The review serves as a valuable resource for researchers to understand the principles and applications of graphs in diverse scientific disciplines.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2023)
Article
Mathematics
Seonghun Kim, Seockhun Bae, Yinhua Piao, Kyuri Jo
Summary: Integrating gene expression data and biological networks into the analysis framework for drug response prediction can improve prediction accuracy. DrugGCN successfully achieves this goal through graph convolutional network technology and demonstrates its success in biological data.
Article
Food Science & Technology
Alberto Nogales, Marcal Mora-Cantallops, Rodrigo Diaz Moron, Alvaro J. Garcia-Tejedor
Summary: This paper presents a quantitative and structural analysis of data on food issues reported by European Union members over the past forty years. The study utilizes statistical measures and network analysis techniques to examine the distribution of contaminated products across countries. The results highlight the different roles played by various countries in detecting problematic origins, such as China or Turkey, while emphasizing the generally good border control policies of European countries in food import/export.
Article
Anatomy & Morphology
Reza Nazari, Mostafa Salehi
Summary: During the prenatal and early postnatal periods, the human brain undergoes rapid growth, establishing a foundation for cognitive and behavioral development. This study used graph theory modeling and network science analysis to investigate the effects of age, gender, weight, and typical/atypical development on brain development. Functional connectomes were obtained from 421 neonates, and the results showed various changes in network properties with age. This research provides novel insights into the maturation of functional brain networks and their relationship with cognitive development and neurodevelopmental disorders.
BRAIN STRUCTURE & FUNCTION
(2023)
Article
Computer Science, Artificial Intelligence
Xovee Xu, Ting Zhong, Ce Li, Goce Trajcevski, Fan Zhou
Summary: This paper presents SI-HDGNN, a novel heterogeneous dynamical graph neural network that quantifies and predicts the long-term impact of scientific papers and individual authors. By capturing the temporal-structural characteristics of papers and authors, as well as their complex interactions and long-term dependencies, SI-HDGNN demonstrates superior performance in predicting scientific impact.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Information Systems
Yuede Ma, Matthias Dehmer, Urs-Martin Kuenzi, Shailesh Tripathi, Modjtaba Ghorbani, Jin Tao, Frank Emmert-Streib
Summary: This paper investigates the usefulness of topological graph measures and finds that many measures fail to solve problems effectively due to the selection of redundant and unfavorable graph invariants, as well as the lack of reflection in defining these measures. The paper extends the debate in the literature and quantitatively studies the usefulness of topological indices by assigning a feature vector to graphs that contains 'useful' properties represented by certain measures. The paper demonstrates examples and compares the usefulness using distance measures and an agglomerative clustering task.
INFORMATION SCIENCES
(2022)
Review
Biochemical Research Methods
Pietro Hiram Guzzi, Francesco Petrizzelli, Tommaso Mazza
Summary: This article discusses the importance of controlling disease spread and the use of computational tools and models to achieve this. Using COVID-19 as an example, it demonstrates how these models can be used to optimize vaccine prioritization strategies and explores their applicability to other diseases.
BRIEFINGS IN BIOINFORMATICS
(2022)