System Biology Approach: Gene Network Analysis for Muscular Dystrophy

  • Federica Censi
  • Giovanni Calcagnini
  • Eugenio Mattei
  • Alessandro Giuliani
Part of the Methods in Molecular Biology book series (MIMB, volume 1687)


Phenotypic changes at different organization levels from cell to entire organism are associated to changes in the pattern of gene expression. These changes involve the entire genome expression pattern and heavily rely upon correlation patterns among genes. The classical approach used to analyze gene expression data builds upon the application of supervised statistical techniques to detect genes differentially expressed among two or more phenotypes (e.g., normal vs. disease). The use of an a posteriori, unsupervised approach based on principal component analysis (PCA) and the subsequent construction of gene correlation networks can shed a light on unexpected behaviour of gene regulation system while maintaining a more naturalistic view on the studied system.

In this chapter we applied an unsupervised method to discriminate DMD patient and controls. The genes having the highest absolute scores in the discrimination between the groups were then analyzed in terms of gene expression networks, on the basis of their mutual correlation in the two groups. The correlation network structures suggest two different modes of gene regulation in the two groups, reminiscent of important aspects of DMD pathogenesis.

Key words

Gene expression Principal component analysis Gene networks Muscular dystrophy 


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Copyright information

© Springer Science+Business Media LLC 2018

Authors and Affiliations

  • Federica Censi
    • 1
  • Giovanni Calcagnini
    • 1
  • Eugenio Mattei
    • 1
  • Alessandro Giuliani
    • 2
  1. 1.Department of Cardiovascular, Dysmetabolic and Aging-associated DiseasesItalian National Institute of HealthRomeItaly
  2. 2.Department of Environment and HealthItalian National Institute of HealthRomeItaly

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