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Network Medicine in the era of Big Data in Science and Healthcare

NetMed Collection © via Pixabay, CC0 Creative CommonsAdvances in the field of network medicine and in complex networks theory allow for a more holistic approach to human health through the study of networks of genes and proteins, modules across cells and tissues, electronic health records, epidemiological and clinical data. Novel concepts and approaches derived from recent progress in network theory, dynamical systems, and computational biology, combined with the large-scale datasets produced from subcellular to social levels are promised to provide new insights into the complex processes involved in human physiology and diseases. This Special Issue focuses on bringing together novel network approaches applied to various biological and health-related datasets and will address the current challenges and bottlenecks towards future major advances by describing findings that can drive the implementation of translational network medicine.

The topics of this special issue include:

  • Biological networks and their applications in healthcare, aging and disease biology
  • Systems pharmacology and drug repurposing
  • Multi-omics / multilayer networks in medicine
  • Precision network medicine for personalized diagnostics and therapy
  • Network-based approaches for undiagnosed or rare diseases
  • Mobility, social network and electronic health record analysis for human well-being
  • Connected objects for health
  • Epidemiological data analysis and network dynamics
  • Network physiology and organ level network

Lead guest editor
Amitabh Sharma, Harvard Medical School, Boston USA
Guest editors
Marc Santolini, Northeastern University, Boston, USA 
Emre Guney, Institute for Biomedical Research, Barcelona, Spain

  1. Electronic healthcare records contain large volumes of unstructured data in different forms. Free text constitutes a large portion of such data, yet this source of richly detailed information often remains und...

    Authors: M. Tarik Altuncu, Erik Mayer, Sophia N. Yaliraki and Mauricio Barahona
    Citation: Applied Network Science 2019 4:2
  2. Tools from network science can be utilized to study relations between diseases. Different studies focus on different types of inter-disease linkages. One of them is the comorbidity patterns derived from large-...

    Authors: Babak Fotouhi, Naghmeh Momeni, Maria A. Riolo and David L. Buckeridge
    Citation: Applied Network Science 2018 3:46
  3. Understanding the relationship between individuals’ social networks and health could help devise public health interventions for reducing incidence of unhealthy behaviors or increasing prevalence of healthy on...

    Authors: Shikang Liu, David Hachen, Omar Lizardo, Christian Poellabauer, Aaron Striegel and Tijana Milenković
    Citation: Applied Network Science 2018 3:45
  4. With the growing ubiquity of data in network form, clustering in the context of a network, represented as a graph, has become increasingly important. Clustering is a very useful data exploratory machine learni...

    Authors: John Matta, Junya Zhao, Gunes Ercal and Tayo Obafemi-Ajayi
    Citation: Applied Network Science 2018 3:38
  5. In this paper, we analyze the millions of referral paths of patients’ interactions with the healthcare system for each year in the 2006-2011 time period and relate them to U.S. cardiovascular treatment records...

    Authors: Chuankai An, A. James O’Malley and Daniel N. Rockmore
    Citation: Applied Network Science 2018 3:20
  6. There is an increasing accumulation of evidence supporting the existence of a hyperbolic geometry underlying the network representation of complex systems. In particular, it has been shown that the latent geom...

    Authors: Franziska Härtner, Miguel A. Andrade-Navarro and Gregorio Alanis-Lobato
    Citation: Applied Network Science 2018 3:10