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Complexity
An interdisciplinary forum for complexity research
Image Credit: Andy Lamb, CC-BY
+ More About This ChannelMost of today’s global challenges, from online misinformation spreading to Ebola outbreaks, involve such a vast number of interacting players that reductionism delivers little insight. Systems are often non-linear, exhibiting complexity in temporal and spatial domains over large scales, which is a challenge to predictability and comprehension. Strategies must be found to look at the problem as a whole, in all its complexity. Representing the associated data as a complex network, in which nodes and connections between them form complicated patterns, is one such strategy. Network science provides novel tools for analyzing, visualizing and modeling this data thanks to the cross-fertilization of fields as diverse as statistical physics, algebraic topology and machine learning, among the others.
This Channel brings together all aspects of complexity research and includes interdisciplinary topics from network theory to applications in neuroscience and the social sciences.
Channel Editors
Image credit
Andy Lamb, CC-BY
Image credit
Andy Lamb, CC-BY
Image credit
Andy Lamb, CC-BY
Channel Items
Showing 1 – 10 of 313 articles
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PLOS Computational Biology Beyond ranking nodes: Predicting epidemic outbreak sizes by network centralities
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PLOS ONE Data-driven network alignment
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PLOS Computational Biology Immunization strategies in networks with missing data
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PLOS Computational Biology EDITOR’S PICK: Data-driven contact structures: From homogeneous mixing to multilayer networks
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PLOS Computational Biology Using information theory to optimise epidemic models for real-time prediction and estimation
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PLOS Computational Biology Estimation of neuron parameters from imperfect observations