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Characterization and modeling of protein–protein interaction networks

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  • Colizza, Vittoria
  • Flammini, Alessandro
  • Maritan, Amos
  • Vespignani, Alessandro

Abstract

The recent availability of high-throughput gene expression and proteomics techniques has created an unprecedented opportunity for a comprehensive study of the structure and dynamics of many biological networks. Global proteomic interaction data, in particular, are synthetically represented as undirected networks exhibiting features far from the random paradigm which has dominated past effort in network theory. This evidence, along with the advances in the theory of complex networks, has triggered an intense research activity aimed at exploiting the evolutionary and biological significance of the resulting network's topology. Here we present a review of the results obtained in the characterization and modeling of the yeast Saccharomyces Cerevisiae protein interaction networks obtained with different experimental techniques. We provide a comparative assessment of the topological properties and discuss possible biases in interaction networks obtained with different techniques. We report on dynamical models based on duplication mechanisms that cast the protein interaction networks in the family of dynamically growing complex networks. Finally, we discuss various results and analysis correlating the networks’ topology with the biological function of proteins.

Suggested Citation

  • Colizza, Vittoria & Flammini, Alessandro & Maritan, Amos & Vespignani, Alessandro, 2005. "Characterization and modeling of protein–protein interaction networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 352(1), pages 1-27.
    • Handle: RePEc:eee:phsmap:v:352:y:2005:i:1:p:1-27
    DOI: 10.1016/j.physa.2004.12.030
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    References listed on IDEAS

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    1. Eugene V. Koonin & Yuri I. Wolf & Georgy P. Karev, 2002. "The structure of the protein universe and genome evolution," Nature, Nature, vol. 420(6912), pages 218-223, November.
    2. Andreas Wagner, 2001. "The Yeast Protein Interaction Network Evolves Rapidly and Contains Few Redundant Duplicate Genes," Working Papers 01-04-022, Santa Fe Institute.
    3. Ergün, G. & Rodgers, G.J., 2002. "Growing random networks with fitness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 303(1), pages 261-272.
    4. David Eisenberg & Edward M. Marcotte & Ioannis Xenarios & Todd O. Yeates, 2000. "Protein function in the post-genomic era," Nature, Nature, vol. 405(6788), pages 823-826, June.
    5. Barabási, Albert-László & Albert, Réka & Jeong, Hawoong, 1999. "Mean-field theory for scale-free random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 272(1), pages 173-187.
    6. Kenneth H. Wolfe & Denis C. Shields, 1997. "Molecular evidence for an ancient duplication of the entire yeast genome," Nature, Nature, vol. 387(6634), pages 708-713, June.
    7. Anton J. Enright & Ioannis Iliopoulos & Nikos C. Kyrpides & Christos A. Ouzounis, 1999. "Protein interaction maps for complete genomes based on gene fusion events," Nature, Nature, vol. 402(6757), pages 86-90, November.
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    Cited by:

    1. Zheng, Xiaolong & Zeng, Daniel & Li, Huiqian & Wang, Feiyue, 2008. "Analyzing open-source software systems as complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(24), pages 6190-6200.
    2. Wang, Difei & Jian, Lirong & Cao, Fengyuan & Xue, Chenyan, 2022. "An extended scale-free network evolution model based on star-like coupling motif embedding," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    3. Ma, A. & Mondragón, R.J., 2012. "Evaluation of network robustness using a node tearing algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(24), pages 6674-6681.

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