Network Analysis and Applications in Pediatric Research

  • Hailong Li
  • Zhaowei Ren
  • Sheng Ren
  • Xinyu Guo
  • Xiaoting Zhu
  • Long Jason Lu
Part of the Translational Bioinformatics book series (TRBIO, volume 10)


Networks, where nodes denote entities and links denote associations, provide a unified representation for a variety of complex systems, from social relationships to molecular interactions. In an era of big data, network analysis has been proved useful in biological applications such as predicting functions of proteins, guiding the design of wet-lab experiments, and discovering biomarkers of diseases. Driven by the availability of large-scale data sets and rapid development of bioinformatics’ tools, the research community has applied network analysis to define underlying causes of pediatric diseases. This will almost certainly lead to more effective strategies for prevention and treatment of diseases. In this chapter, we will introduce classic and the state-of-the-art network analysis methodologies, approaches and their applications. We then provide four examples of recent research, where network analysis is being applied in pediatrics. These include the identification of high-density lipoprotein particles that underlie the development of cardiovascular disease using protein-protein interaction networks, alternative splicing analysis by splicing interaction network, construction and network analysis of pediatric brain functional atlas, and disease relationship exploration using diagnosis association networks constructed by electronic health record.


Network analysis Network applications Network prediction Pediatric diseases 


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Copyright information

© Springer Science+Business Media Singapore 2016

Authors and Affiliations

  • Hailong Li
    • 1
  • Zhaowei Ren
    • 1
    • 2
  • Sheng Ren
    • 1
    • 3
  • Xinyu Guo
    • 1
    • 2
  • Xiaoting Zhu
    • 1
    • 2
  • Long Jason Lu
    • 2
    • 4
    • 5
    • 1
  1. 1.Division of Biomedical InformaticsCincinnati Children’s Hospital Medical CenterCincinnatiUSA
  2. 2.Department of Electrical Engineering and Computing SystemsUniversity of CincinnatiCincinnatiUSA
  3. 3.Department of StatisticsUniversity of CincinnatiCincinnatiUSA
  4. 4.Department of Environmental HealthUniversity of CincinnatiCincinnatiUSA
  5. 5.Departments of Pediatrics and Biomedical Informatics, Division of Biomedical InformaticsCincinnati Children’s Hospital Research FoundationCincinnatiUSA

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