A Relevance Index Method to Infer Global Properties of Biological Networks

  • Marco Villani
  • Laura Sani
  • Michele Amoretti
  • Emilio Vicari
  • Riccardo Pecori
  • Monica Mordonini
  • Stefano Cagnoni
  • Roberto Serra
Conference paper
First Online:
Part of the Communications in Computer and Information Science book series (CCIS, volume 830)

Abstract

Many complex systems, both natural and artificial, may be represented by networks of interacting nodes. Nevertheless, it is often difficult to find meaningful correspondences between the dynamics expressed by these systems and the topological description of their networks. In contrast, many of these systems may be well described in terms of coordinated behavior of their dynamically relevant parts. In this paper we use the recently proposed Relevance Index approach, based on information-theoretic measures. Starting from the observation of the dynamical states of any system, the Relevance Index is able to provide information about its organization. Moreover, we show how the application of the proposed approach leads to novel and effective interpretations in the T helper network case study.

Keywords

Complex systems Biological networks Dynamical behavior Relevance index T helper cells 
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Notes

Acknowledgments

The work of Michele Amoretti was supported by the University of Parma Research Fund - FIL 2016 - Project “NEXTALGO: Efficient Algorithms for Next-Generation Distributed Systems”.

This work greatly benefited from discussions with Andrea Roli, to whom the authors are warmly thankful.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Marco Villani
    • 2
  • Laura Sani
    • 1
  • Michele Amoretti
    • 1
  • Emilio Vicari
    • 4
  • Riccardo Pecori
    • 1
    • 3
  • Monica Mordonini
    • 1
  • Stefano Cagnoni
    • 1
  • Roberto Serra
    • 2
  1. 1.Dip. di Ingegneria e ArchitetturaUniversità di ParmaParmaItaly
  2. 2.Dip. Scienze Fisiche, Informatiche e MatematicheUniversità di Modena e Reggio EmiliaModenaItaly
  3. 3.SMARTEST Research CentreUniversità eCAMPUSNovedrateItaly
  4. 4.Camlin ItalyParmaItaly

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