Evidence map›Paper›PMID 26050708›Full record

ArticleBMC systems biology2015

The hierarchical organization of natural protein interaction networks confers self-organization properties on pseudocells.

Eugenia Galeota, Caius Gravila, Filippo Castiglione, Massimo Bernaschi, Gianni Cesareni

Abstract read
In one paragraph

Article in BMC systems biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Eugenia Galeota
Caius Gravila
Filippo Castiglione
Massimo Bernaschi
Gianni Cesareni

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCell organization is governed and maintained via specific interactions among its constituent macromolecules. Comparison of the experimentally determined protein interaction networks in different model organisms has revealed little conservation of the specific edges linking ortholog proteins. Nevertheless, some topological characteristics of the graphs representing the networks--namely non-random degree distribution and high clustering coefficient--are shared by networks of distantly related organisms. Here we investigate the role of the topological features of the protein interaction network in promoting cell organization.

methodsWe have used a stochastic model, dubbed ProtNet representing a computer stylized cell to answer questions about the dynamic consequences of the topological properties of the static graphs representing protein interaction networks.

resultsBy using a novel metrics of cell organization, we show that natural networks, differently from random networks, can promote cell self-organization. Furthermore the ensemble of protein complexes that forms in pseudocells, which self-organize according to the interaction rules of natural networks, are more robust to perturbations.

conclusionsThe analysis of the dynamic properties of networks with a variety of topological characteristics lead us to conclude that self organization is a consequence of the high clustering coefficient, whereas the scale free degree distribution has little influence on this property.

Indexed as

Cell Physiological PhenomenaModels, BiologicalProtein Interaction MapsSystems Biology

Identifiers

PMID26050708
PMCPMC4464023

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.