Multilayer Analysis and Visualization of Networks
By Manlio De Domenico, M. A. Porter, Alex Arenas. J. Complex Networks, 2014
403 citations recorded by the source corpus.
Multilayer relationships among entities and information about entities must be accompanied by the means to analyse, visualize and obtain insights from such data. We present open-source software (muxViz) that contains a collection of algorithms for the analysis of multilayer networks, which are an important way to represent a large variety of complex systems throughout science and engineering. We demonstrate the ability of muxViz to analyse and interactively visualize multilayer data using empirical genetic, neuronal and transportation networks. Our software is available at https://github.com/manlius/muxViz.
Subfields: Cognitive Neuroscience, Computer Vision and Pattern Recognition, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/499d11a3929db6d5b9aa1324c40bd6970d0c39e8
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cognitive Neuroscience
- M. A. Porter
- Alex Arenas
- Marc Barthelemy
- Matjaz Perc
- Yamir Moreno
- Marko Marhl
- Olaf Sporns
- Jürgen Kurths
In Computer Vision and Pattern Recognition
In Molecular Biology
- M. A. Porter
- Alex Arenas
- Yamir Moreno
- Mikko Kivelä
- J. P. Gleeson
- Marc Barthelemy
- Matjaz Perc
- Santo Fortunato
Citations in the corpus
- Multilayer networks (2013, methodology): “[138,139] for software for the investigation and visualization of multilayer networks.”
- Network science of biological systems at different scales: A review. (2017, background): “biochemical reactions, are actually highly interdependent and are as such excellent candidates for being analyzed and visualized as MLN [23,131,149] Moreover, the increased availability of genomic, proteomic and metabolomic data made the task of integrating multilayered complexity of biological…”