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Evolving Protein Interaction Networks through Gene Duplication

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Author Info
Romualdo Pastor-Satorras
Eric Smith
Ricard V. Solé
Abstract

The topology of the proteome map revealed by recent large-scale hybridization methods has shown that the distribution of protein-protein interactions is highly heterogeneous, with many proteins having few links while a few of them are heavily connected. This particular topology is shared by other cellular networks, such as metabolic pathways, and it has been suggested to be responsible for the high mutational homeostasis displayed by the genome of some organisms. In this paper we explore a recent model of proteome evolution that has been shown to reproduce many of the features displayed by its real counterparts. The model is based on gene duplication plus re-wiring of the newly created genes. The statistical features displayed by the proteome of well-known organisms are reproduced, suggesting that the overall topology of the protein maps naturally emerges from the two leading mechanisms considered by the model.

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Paper provided by Santa Fe Institute in its series Working Papers with number 02-02-008.

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Date of creation: Feb 2002
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Handle: RePEc:wop:safiwp:02-02-008

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Related research
Keywords: Proteomics; genomics; genome evolution; complex networks; scaling;

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  1. Ramon Ferrer i Cancho & Ricard V. Solé, 2001. "Optimization in Complex Networks," Working Papers 01-11-068, Santa Fe Institute.
  2. Ramon Ferrer i Cancho & Ricard V. Solé, 2001. "The Small-World of Human Language," Working Papers 01-03-016, Santa Fe Institute.
  3. Andreas Wagner, 2001. "The Yeast Protein Interaction Network Evolves Rapidly and Contains Few Redundant Duplicate Genes," Working Papers 01-04-022, Santa Fe Institute.
  4. Richard J. Williams & Neo D. Martinez & Eric L. Berlow & Jennifer A. Dunne & Albert-Laszlo Barabasi, 2001. "Two Degrees of Separation in Complex Food Webs," Working Papers 01-07-036, Santa Fe Institute.
  5. Andreas Wagner, 2001. "Estimating Coarse Gene Network Structure from Large-Scale Gene Perturbation Data," Working Papers 01-09-051, Santa Fe Institute.
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