A node-based informed modularity strategy to identify organizational modules in anatomical networks.

ABSTRACT: The study of morphological modularity using anatomical networks is growing in recent years. A common strategy to find the best network partition uses community detection algorithms that optimize the modularity Q function. Because anatomical networks and their modules tend to be small, this strategy often produces two problems. One is that some algorithms find inexplicable different modules when one inputs slightly different networks. The other is that algorithms find asymmetric modules in otherwise symmetric networks. These problems have discouraged researchers to use anatomical network analysis and boost criticisms to this methodology. Here, I propose a node-based informed modularity strategy (NIMS) to identify modules in anatomical networks that bypass resolution and sensitivity limitati

SUBMITTER: Esteve-Altava B 

PROVIDER: S-EPMC7595689 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature