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  1. Connecting the Dots: Anatomical Network Analysis in Morphological EvoDevo.Diego Rasskin-Gutman & Borja Esteve-Altava - 2014 - Biological Theory 9 (2):178-193.
    Morphological EvoDevo is a field of biological inquiry in which explicit relations between evolutionary patterns and growth or morphogenetic processes are made. Historically, morphological EvoDevo results from the coming together of several traditions, notably Naturphilosophie, embryology, the study of heterochrony, and developmental constraints. A special feature binding different approaches to morphological EvoDevo is the use of formalisms and mathematical models. Here we will introduce anatomical network analysis, a new approach centered on connectivity patterns formed by anatomical parts, with its own (...)
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  • Overlapping communities and roles in networks with node attributes: Probabilistic graphical modeling, Bayesian formulation and variational inference.Gianni Costa & Riccardo Ortale - 2022 - Artificial Intelligence 302 (C):103580.
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  • A network approach to the French system of legal codes—part I: analysis of a dense network. [REVIEW]Romain Boulet, Pierre Mazzega & Danièle Bourcier - 2011 - Artificial Intelligence and Law 19 (4):333-355.
    We explore one aspect of the structure of a codified legal system at the national level using a new type of representation to understand the strong or weak dependencies between the various fields of law. In Part I of this study, we analyze the graph associated with the network in which each French legal code is a vertex and an edge is produced between two vertices when a code cites another code at least one time. We show that this network (...)
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  • Network and Multilayer Network Approaches to Understanding Human Brain Dynamics.Sarah Feldt Muldoon & Danielle S. Bassett - 2016 - Philosophy of Science 83 (5):710-720.
    Network neuroscience provides a systems approach to the study of the brain and enables the examination of interactions measured at different temporal and spatial scales. We review current methods to quantify the structure of brain networks and compare that structure across different clinical cohorts, cognitive states, and subjects. We further introduce the emerging mathematical concept of multilayer networks and describe the advantages of this approach to model changing brain dynamics over time. We conclude by offering several concrete examples of how (...)
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