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This web collection showcases the potential of interdisciplinary complexity research by bringing together a selection of recent Nature Communications articles investigating complex systems. Complexity research aims to characterize and understand the behaviour and nature of systems made up of many interacting elements. Such efforts often require interdisciplinary collaboration and expertise from diverse schools of thought. Nature Communications publishes papers across a broad range of topics that span the physical and life sciences, making the journal an ideal home for interdisciplinary studies.
The Ecology and evolution section contains studies that explore the dynamics of networks of genes, individuals and communities using combinations of empirical data and mathematical tools. Other examples of computational modeling in biology include studies on precision medicine and molecular network dynamics, and these are highlighted in Network medicine tab. Neuroscience is another discipline that is effectively leveraging network analysis to better understand how the complex interactions between neuroanatomy and function give rise to equally complex human behaviors. Such behaviors, when combined, give rise to cultures and societies. The latter are paradigmatic complex systems, and articles presented in the Social systems section examine these paradigmatic complex systems, describing the dynamics of social systems, financial systems and transport networks that affect much of our daily lives. Finally, the collection under the Network structure and dynamics tab showcases methodological advances in complex system modeling and network analysis. The articles that we felt represented each section particularly well are also available in the Editors' picks section, below.
Solving some of the most important problems in science may only be possible when scientists with different backgrounds collaborate to address shared questions using complementary techniques. Truly interdisciplinary research that can bridge the natural, physical and social sciences remains challenging, as it requires scientists to share and discuss their views across disciplines, and therefore such research must also be able to reach a diverse audience. Our collection, which has been chosen by editors across the broad spectrum of subjects covered by Nature Communications, has been put together with this specific goal in mind.
Cancer is caused by accumulating genetic mutations. Here, the authors investigate the cooperative effect of these mutations in colorectal cancer patients and identify a giant cluster of mutation-propagating modules that undergoes percolation transition during tumorigenesis.
Complex networks can be used to model brain networks. Here the authors identify the essential nodes in a model of a brain network and then validate these predictions by means of in vivo pharmacogenetic interventions. They find that the nucleus accumbens is a central region for brain integration.
The structure and dynamics of microbial communities reflect trade-offs in the ability to use different resources. Here, Josephides and Swain incorporate metabolic trade-offs into an eco-evolutionary model to predict networks of mutational paths and the evolutionary outcomes for microbial communities.
The probability that a region will develop a particular research activity increases with the number of similar activities in neighboring regions. Here the authors analyze diffusion strategies and show that it is not only important to know which activities to target but also when to target them.
Complex networks are a useful tool to investigate spreading processes but topology alone is insufficient to predict information flow. Here the authors propose a measure of information flow and predict its behavior from the interplay between structure and dynamics.
Complex networks are a useful tool to investigate the structure of cities and their street networks. Here the authors investigate the shape of travel routes in 92 cities and define a metric called inness which reveals connections between common urban features in cities with similar inness profiles.
Human brain development is characterized by an increased control of neural activity, but how this happens is not well understood. Here, authors show that white matter connectivity in 882 youth, aged 8-22, becomes increasingly specialized locally and is optimized for network control.
Robust perfect adaptation (RPA), the ability of a system to return to its pre-stimulus state in the presence of a new signal, enables organisms to respond to further changes in stimuli. Here, the authors identify the modular structure of the full set of network topologies that can confer RPA on complex networks.
Species interaction networks have been usually delimited by perceived habitat borders. Here, seed-dispersal is analyzed as a regional multilayer network of interconnected habitats, highlighting the key role of versatile dispersers for the functional cohesion of the whole Gorongosa landscape.
Mouse digit patterning is controlled by a Turing network of Bmp, Sox9, and Wnt. Here, Onimaru et al. show that fin patterning in the catshark, Scyliorhinus canicula, is controlled by the same network with a different spatial organization; thus, the Turing network is deeply conserved in limb development.
Understanding the dynamics of empirical food webs is of central importance for predicting the stability of ecological communities. Here Allesina et al.derive an approximation to accurately predict the stability of large food webs whose structure is built using the cascade model.
Attempts to predict novel use for existing drugs rarely consider information on the impact on the genes perturbed in a given disease. Here, the authors present a novel network-based drug-disease proximity measure that provides insight on gene specific therapeutic effect of drugs and may facilitate drug repurposing.
The hippocampus is known to support navigation, but how it processes possible paths to aid navigation is unknown. Here Javadiet al. show that entering streets drives hippocampal activity corresponding to the number of future paths, and that prefrontal activity corresponds to path-planning demands.
Proximity to criticality can be advantageous under changing conditions, but it also entails reduced robustness. Here, the authors analyse fight sizes in a macaque society and find not only that it sits near criticality, but also that the distance from the critical point is tunable through adjustment of individual behaviour and social conflict management.
The spread of instabilities in financial systems, similarly to ecosystems, is influenced by topological features of the underlying network structures. Here the authors show, independently of specific financial models, that market integration and diversification can drive the system towards instability.
It is believed that patterns of social ties are related to individuals’ financial status. Here the authors substantiate this concept by quantitatively demonstrating that a measure of an individual’s location and influence within their social network can be used to infer their economic wellness.
Some argue that health-related behaviours, such as obesity, are contagious, but empirical evidence of health contagion remains inconclusive. Here, using a large scale quasi-experiment in a global network of runners, Aral and Nicolaides show that this type of contagion exists in fitness behaviours.
Complex networks have been conjectured to be hidden in metric spaces, which offer geometric interpretation of networks’ topologies. Here the authors extend this concept to weighted networks, providing empirical evidence on the metric natures of weights, which are shown to be reproducible by a gravity model.