dorsal/arxiv
View SchemaProbability Models for Degree Distributions of Protein Interaction Networks
| Authors | Michael P. H. Stumpf, Piers J. Ingram |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0507005 |
| URL | https://arxiv.org/abs/q-bio/0507005 |
| DOI | 10.1209/epl/i2004-10531-8 |
| Journal | Europhys.Lett., 71 (1), pp. 152-158 (2005) |
Abstract
The degree distribution of many biological and technological networks has been described as a power-law distribution. While the degree distribution does not capture all aspects of a network, it has often been suggested that its functional form contains important clues as to underlying evolutionary processes that have shaped the network. Generally, the functional form for the degree distribution has been determined in an ad-hoc fashion, with clear power-law like behaviour often only extending over a limited range of connectivities. Here we apply formal model selection techniques to decide which probability distribution best describes the degree distributions of protein interaction networks. Contrary to previous studies this well defined approach suggests that the degree distribution of many molecular networks is often better described by distributions other than the popular power-law distribution. This, in turn, suggests that simple, if elegant, models may not necessarily help in the quantitative understanding of complex biological processes.\
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"abstract": "The degree distribution of many biological and technological networks has\nbeen described as a power-law distribution. While the degree distribution does\nnot capture all aspects of a network, it has often been suggested that its\nfunctional form contains important clues as to underlying evolutionary\nprocesses that have shaped the network. Generally, the functional form for the\ndegree distribution has been determined in an ad-hoc fashion, with clear\npower-law like behaviour often only extending over a limited range of\nconnectivities. Here we apply formal model selection techniques to decide which\nprobability distribution best describes the degree distributions of protein\ninteraction networks. Contrary to previous studies this well defined approach\nsuggests that the degree distribution of many molecular networks is often\nbetter described by distributions other than the popular power-law\ndistribution. This, in turn, suggests that simple, if elegant, models may not\nnecessarily help in the quantitative understanding of complex biological\nprocesses.\\",
"arxiv_id": "q-bio/0507005",
"authors": [
"Michael P. H. Stumpf",
"Piers J. Ingram"
],
"categories": [
"q-bio.MN"
],
"doi": "10.1209/epl/i2004-10531-8",
"journal_ref": "Europhys.Lett., 71 (1), pp. 152-158 (2005)",
"title": "Probability Models for Degree Distributions of Protein Interaction Networks",
"url": "https://arxiv.org/abs/q-bio/0507005"
},
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