Network Modularity and Robustness

2016 ◽  
pp. 252-279
Keyword(s):  
Network Modularity

Cortical network modularity changes along the course of frontotemporal and Alzheimer's dementing diseases

2021 ◽  
Vol 429 ◽  
pp. 118988
Author(s):  
Laura Bonanni ◽  
Raffaella Franciotti ◽  
Davide Moretti ◽  
Alberto Benussi ◽  
Laura Ferri ◽  
...  
Keyword(s):  
Cortical Network ◽  
Network Modularity

scholarly journals An a posteriori measure of network modularity

F1000Research ◽  
2013 ◽  
Vol 2 ◽  
pp. 130 ◽  
Author(s):  
Timothée Poisot
Keyword(s):  
Real World ◽  
Ecological Networks ◽  
A Posteriori ◽  
Large Dataset ◽  
Network Modularity

Measuring modularity is important to understand the structure of networks, and has an important number of real-world implications. However, several measures exists to assess the modularity, and give both different modularity values and different modules composition. In this article, I propose an a posteriori measure of modularity, which represents the ratio of interactions between members of the same modules vs. members of different modules. I apply this measure to a large dataset of 290 ecological networks, to show that it gives new insights about their modularity.

Community detection in complex networks by using membrane algorithm

2018 ◽  
Vol 29 (01) ◽  
pp. 1850003 ◽  
Author(s):  
Chuang Liu ◽  
Linan Fan ◽  
Zhou Liu ◽  
Xiang Dai ◽  
Jiamei Xu ◽  
...  
Keyword(s):  
Network Analysis ◽  
Complex Networks ◽  
Community Detection ◽  
Membrane Structure ◽  
Superior Performance ◽  
Membrane Systems ◽  
Membrane Algorithm ◽  
Differential Evolutionary Algorithm ◽  
Network Modularity

Community detection in complex networks is a key problem of network analysis. In this paper, a new membrane algorithm is proposed to solve the community detection in complex networks. The proposed algorithm is based on membrane systems, which consists of objects, reaction rules, and a membrane structure. Each object represents a candidate partition of a complex network, and the quality of objects is evaluated according to network modularity. The reaction rules include evolutionary rules and communication rules. Evolutionary rules are responsible for improving the quality of objects, which employ the differential evolutionary algorithm to evolve objects. Communication rules implement the information exchanged among membranes. Finally, the proposed algorithm is evaluated on synthetic, real-world networks with real partitions known and the large-scaled networks with real partitions unknown. The experimental results indicate the superior performance of the proposed algorithm in comparison with other experimental algorithms.

scholarly journals The role of marine mammals in the Barents Sea foodweb

2019 ◽  
Vol 76 (Supplement_1) ◽  
pp. i37-i53 ◽  
Author(s):  
Marie-Anne Blanchet ◽  
Raul Primicerio ◽  
André Frainer ◽  
Susanne Kortsch ◽  
Mette Skern-Mauritzen ◽  
...  
Keyword(s):  
Marine Mammals ◽  
Barents Sea ◽  
Phylogenetic Group ◽  
The Arctic ◽  
Phylogenetic Groups ◽  
Baleen Whales ◽  
Trophic Links ◽  
The Barents Sea ◽  
Network Modularity

Abstract Marine mammals are important players in the Barents Sea ecosystem but their structural role in the foodweb has been little explored. We compare foodweb-related characteristics within and between phylogenetic groups for 19 marine mammals. As a group, they directly connect to the most central species (i.e cod and haddock) in the Barents Sea (i.e. cod and haddock) and consume over half of the available species. Pinnipeds are the most homogenous phylogenetic group with high omnivory and high prey richness. Mysticetes are split between well-connected species with high omnivory like the humpback whale, and peripheral specialists like the blue whale. Based on foodweb-derived indices some species consistently cluster together forming two groups, suggesting topological redundancy within them. One is dominated by Arctic seals and the other includes most of the baleen whales. Marine mammals generally contribute to network modularity as their trophic links are mainly within their own module. However, Atlantic species such as the grey seal act as a module connector decreasing modularity. This might negatively affect ecosystem robustness with perturbation effects spreading further and quicker in the foodweb. In the Arctic reaches of the Barents Sea, climate warming is likely to bring about extensive changes in the foodweb structure through a redistribution of species.

scholarly journals Brain Network Modularity During a Sustained Working-Memory Task

2020 ◽  
Vol 11 ◽  
Author(s):  
Marta Moraschi ◽  
Daniele Mascali ◽  
Silvia Tommasin ◽  
Tommaso Gili ◽  
Ibrahim Eid Hassan ◽  
...  
Keyword(s):  
Working Memory ◽  
Memory Task ◽  
Brain Network ◽  
Network Modularity

scholarly journals A multi-shell multi-tissue diffusion study of brain connectivity in early multiple sclerosis

2019 ◽  
Vol 26 (7) ◽  
pp. 774-785 ◽  
Author(s):  
Carmen Tur ◽  
Francesco Grussu ◽  
Ferran Prados ◽  
Thalis Charalambous ◽  
Sara Collorone ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Brain Connectivity ◽  
Diffusion Imaging ◽  
Orientation Distribution ◽  
Distribution Functions ◽  
Network Modularity ◽  
Clinical Measures ◽  
Network Metrics ◽  
Better Than ◽  
Single Shell

Background: The potential of multi-shell diffusion imaging to produce accurate brain connectivity metrics able to unravel key pathophysiological processes in multiple sclerosis (MS) has scarcely been investigated. Objective: To test, in patients with a clinically isolated syndrome (CIS), whether multi-shell imaging-derived connectivity metrics can differentiate patients from controls, correlate with clinical measures, and perform better than metrics obtained with conventional single-shell protocols. Methods: Nineteen patients within 3 months from the CIS and 12 healthy controls underwent anatomical and 53-direction multi-shell diffusion-weighted 3T images. Patients were cognitively assessed. Voxel-wise fibre orientation distribution functions were estimated and used to obtain network metrics. These were also calculated using a conventional single-shell diffusion protocol. Through linear regression, we obtained effect sizes and standardised regression coefficients. Results: Patients had lower mean nodal strength ( p = 0.003) and greater network modularity than controls ( p = 0.045). Greater modularity was associated with worse cognitive performance in patients, even after accounting for lesion load ( p = 0.002). Multi-shell-derived metrics outperformed single-shell-derived ones. Conclusion: Connectivity-based nodal strength and network modularity are abnormal in the CIS. Furthermore, the increased network modularity observed in patients, indicating microstructural damage, is clinically relevant. Connectivity analyses based on multi-shell imaging can detect potentially relevant network changes in early MS.

scholarly journals Spectral Characterization of Hierarchical Network Modularity and Limits of Modularity Detection

PLoS ONE ◽  
2013 ◽  
Vol 8 (1) ◽  
pp. e54383 ◽  
Author(s):  
Somwrita Sarkar ◽  
James A. Henderson ◽  
Peter A. Robinson
Keyword(s):  
Spectral Characterization ◽  
Hierarchical Network ◽  
Network Modularity

Using a network modularity analysis to inform management of a rare endemic plant in the northern Great Plains, USA

2014 ◽  
Vol 51 (4) ◽  
pp. 1024-1032 ◽  
Author(s):  
Diane L. Larson ◽  
Sam Droege ◽  
Paul A. Rabie ◽  
Jennifer L. Larson ◽  
Jelle Devalez ◽  
...  
Keyword(s):  
Great Plains ◽  
Northern Great Plains ◽  
Endemic Plant ◽  
Modularity Analysis ◽  
Network Modularity ◽  
Rare Endemic
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