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Random Graphs and Their Subgraphs

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Discrete and Continuous Models in the Theory of Networks

Part of the book series: Operator Theory: Advances and Applications ((OT,volume 281))

Abstract

Random graphs are more and more used for modeling real world networks such as evolutionary networks of proteins. For this purpose we look at two different models and analyze how properties like connectedness and degree distributions are inherited by differently constructed subgraphs. We also give a formula for the variance of the degrees of fixed nodes in the preferential attachment model and additionally draw a connection between weighted graphs and electrical networks.

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References

  1. A.-L. Barabási and R. Albert. Emergence of scaling in random networks. Science, 286(5439):509–512, 1999.

    Article  MathSciNet  Google Scholar 

  2. M. Bastian, S. Heymann, and M. Jacomy. Gephi: An open source software for exploring and manipulating networks, 2009. http://www.aaai.org/ocs/index.php/ICWSM/09/paper/view/154.

  3. B. Bollobás. Modern Graph Theory. Springer, 1998.

    Book  Google Scholar 

  4. P. Erdős and A. Rényi. On random graphs I. Publ. Math. Debrecen, 6:290–297, 1959.

    Google Scholar 

  5. P. Erdős and A. Rényi. On the evolution of random graphs. Publ. Math. Inst. Hung. Acad. Sci., 5(1):17–60, 1960.

    Google Scholar 

  6. P. Erdős and A. Rényi. On the evolution of random graphs. Bull. Inst. Internat. Statist., 38(4):343–347, 1961.

    Google Scholar 

  7. P. Frisco. Network model with structured nodes. Physical Review, 84(2):021931, 2011.

    Google Scholar 

  8. W. H. Hayt Jr., J. E. Kemmerly, and S. M. Durbin. Engineering Circuit Analysis. The McGraw-Hill Companies, Inc., 8. edition, 2012.

    Google Scholar 

  9. R Development Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, 2008. ISBN 3-900051-07-0, http://www.R-project.org.

  10. P. Tetali. Random walks and the effective resistance of networks. Journal of Theoretical Probability, 4(1):101–109, 1991.

    Article  MathSciNet  Google Scholar 

  11. R. van der Hofstad. Random Graphs and Comples Networks Volume I. Cambridge University Press, 2017.

    Book  Google Scholar 

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Correspondence to Klemens Taglieber .

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Taglieber, K., Freiberg, U. (2020). Random Graphs and Their Subgraphs. In: Atay, F., Kurasov, P., Mugnolo, D. (eds) Discrete and Continuous Models in the Theory of Networks. Operator Theory: Advances and Applications, vol 281. Birkhäuser, Cham. https://doi.org/10.1007/978-3-030-44097-8_16

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