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  Estimating the size of the human interactome

Stumpf, M. P. H., Thorne, T., de Silva†, E., Ronald, S., An, H. J., Lappe, M., et al. (2008). Estimating the size of the human interactome. Proceedings of the Academy of Sciences of the United States of America, 105(19), 6959-6964. doi:10.1073/pnas.0708078105.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-7FDF-F Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-7FE0-9
Genre: Journal Article
Alternative Title : Proc Natl Acad Sci U S A

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 Creators:
Stumpf, Michael P. H., Author
Thorne, Thomas, Author
de Silva†, Eric, Author
Ronald, Stewart, Author
An, Hyeong Jun1, Author
Lappe, Michael2, Author              
Wiuf, Carsten, Author
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1Max Planck Society, ou_persistent13              
2Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433554              

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 Abstract: After the completion of the human and other genome projects it emerged that the number of genes in organisms as diverse as fruit flies, nematodes, and humans does not reflect our perception of their relative complexity. Here, we provide reliable evidence that the size of protein interaction networks in different organisms appears to correlate much better with their apparent biological complexity. We develop a stable and powerful, yet simple, statistical procedure to estimate the size of the whole network from subnet data. This approach is then applied to a range of eukaryotic organisms for which extensive protein interaction data have been collected and we estimate the number of interactions in humans to be approximately 650,000. We find that the human interaction network is one order of magnitude bigger than the Drosophila melanogaster interactome and approximately 3 times bigger than in Caenorhabditis elegans.

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Language(s): eng - English
 Dates: 2008-05-13
 Publication Status: Published in print
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Title: Proceedings of the Academy of Sciences of the United States of America
  Alternative Title : Proc Natl Acad Sci U S A
Source Genre: Journal
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Pages: - Volume / Issue: 105 (19) Sequence Number: - Start / End Page: 6959 - 6964 Identifier: ISSN: 1091-6490