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Networks in life: scaling properties and eigenvalue spectra

Author

Listed:
  • Farkas, I
  • Derényi, I
  • Jeong, H
  • Néda, Z
  • Oltvai, Z.N
  • Ravasz, E
  • Schubert, A
  • Barabási, A.-L
  • Vicsek, T

Abstract

We analyze growing networks ranging from collaboration graphs of scientists to the network of similarities defined among the various transcriptional profiles of living cells. For the explicit demonstration of the scale-free nature and hierarchical organization of these graphs, a deterministic construction is also used. We demonstrate the use of determining the eigenvalue spectra of sparse random graph models for the categorization of small measured networks.

Suggested Citation

  • Farkas, I & Derényi, I & Jeong, H & Néda, Z & Oltvai, Z.N & Ravasz, E & Schubert, A & Barabási, A.-L & Vicsek, T, 2002. "Networks in life: scaling properties and eigenvalue spectra," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 314(1), pages 25-34.
    • Handle: RePEc:eee:phsmap:v:314:y:2002:i:1:p:25-34
    DOI: 10.1016/S0378-4371(02)01181-0
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    1. Barabási, Albert-László & Ravasz, Erzsébet & Vicsek, Tamás, 2001. "Deterministic scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(3), pages 559-564.
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    Cited by:

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    2. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.

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