Randomization and Feedback Properties of Directed Graphs Inspired by Gene Networks

  • M. Cosentino Lagomarsino
  • P. Jona
  • B. Bassetti
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4210)


Having in mind the large-scale analysis of gene regulatory networks, we review a graph decimation algorithm, called “leaf-removal”, which can be used to evaluate the feedback in a random graph ensemble. In doing this, we consider the possibility of analyzing networks where the diagonal of the adjacency matrix is structured, that is, has a fixed number of nonzero entries. We test these ideas on a network model with fixed degree, using both numerical and analytical calculations. Our results are the following. First, the leaf-removal behavior for large system size enables to distinguish between different regimes of feedback. We show their relations and the connection with the onset of complexity in the graph. Second, the influence of the diagonal structure on this behavior can be relevant.


Adjacency Matrix Random Graph Gene Regulatory Network Oriented Graph Simple Cycle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • M. Cosentino Lagomarsino
    • 1
    • 2
  • P. Jona
    • 3
  • B. Bassetti
    • 2
    • 4
  1. 1.UMR 168 / Institut CurieParisFrance
  2. 2.Dip. FisicaUniversità degli Studi di MilanoMilanoItaly
  3. 3.Dip. FisicaPolitecnico di MilanoMilanoItaly
  4. 4.I.N.F.N. MilanoItaly

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