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Complexity Research in Nature Communications

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.  

 

Editors' picks

  • Nature Communications | Article | open

    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.

    • Dongkwan Shin
    • , Jonghoon Lee
    • , Jeong-Ryeol Gong
    •  &  Kwang-Hyun Cho
  • Nature Communications | Article | open

    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.

    • Gino Del Ferraro
    • , Andrea Moreno
    • , Byungjoon Min
    • , Flaviano Morone
    • , Úrsula Pérez-Ramírez
    • , Laura Pérez-Cervera
    • , Lucas C. Parra
    • , Andrei Holodny
    • , Santiago Canals
    •  &  Hernán A. Makse
  • Nature Communications | Article | open

    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.

    • Christos Josephides
    •  &  Peter S. Swain
  • Nature Communications | Article | open

    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.

    • Uzi Harush
    •  &  Baruch Barzel
  • Nature Communications | Article | open

    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.

    • Minjin Lee
    • , Hugo Barbosa
    • , Hyejin Youn
    • , Petter Holme
    •  &  Gourab Ghoshal