Evolving Protein Interaction Networks through Gene Duplication
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.
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
|Date of creation:||Feb 2002|
|Date of revision:|
|Contact details of provider:|| Postal: 1399 Hyde Park Road, Santa Fe, New Mexico 87501|
Web page: http://www.santafe.edu/sfi/publications/working-papers.html
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- Andreas Wagner, 2001. "Estimating Coarse Gene Network Structure from Large-Scale Gene Perturbation Data," Working Papers 01-09-051, Santa Fe Institute.
When requesting a correction, please mention this item's handle: RePEc:wop:safiwp:02-02-008. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Thomas Krichel)
If references are entirely missing, you can add them using this form.