Evidence map›Paper›PMID 22530615›Full record

ArticleBMC genomics2012

Functional organization and its implication in evolution of the human protein-protein interaction network.

Yiqiang Zhao, Sean D Mooney

Abstract read
In one paragraph

Article in BMC genomics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yiqiang ZhaoBuck Institute for Research on Aging, Novato, California, USA.
Sean D Mooney

Funding

STANFORD COMPOSITE(RMI)U54HG004028 · NHGRI · STANFORD UNIVERSITY · PI MUSEN, MARK A · 2005 to 2014
$36.2M
Informatic Profiling of Clinically Relevant MutationR01LM009722 · NLM · UNIVERSITY OF WASHINGTON · PI MOONEY, SEAN DAVID · 2007 to 2014
$3.5M
NCI NIH HHS U54-CA0126540NHGRI NIH HHS U54 HG004028NHGRI NIH HHS U54-HG004028NLM NIH HHS R01 LM009722NLM NIH HHS R01LM009722
6 · The paper itself

Abstract

backgroundBased on the distinguishing properties of protein-protein interaction networks such as power-law degree distribution and modularity structure, several stochastic models for the evolution of these networks have been purposed, motivated by the idea that a validated model should reproduce similar topological properties of the empirical network. However, being able to capture topological properties does not necessarily mean it correctly reproduces how networks emerge and evolve. More importantly, there is already evidence suggesting functional organization and significance of these networks. The current stochastic models of evolution, however, grow the network without consideration for biological function and natural selection.

resultsTo test whether protein interaction networks are functionally organized and their impacts on the evolution of these networks, we analyzed their evolution at both the topological and functional level. We find that the human network is shown to be functionally organized, and its function evolves with the topological properties of the network. Our analysis suggests that function most likely affects local modularity of the network. Consistently, we further found that the topological unit is also the functional unit of the network.

conclusionWe have demonstrated functional organization of a protein interaction network. Given our observations, we suggest that its significance should not be overlooked when studying network evolution.

Indexed as

Computational BiologyEvolution, MolecularProtein Interaction MapsHumansModels, BiologicalPhylogeny

Identifiers

PMID22530615
PMCPMC3375200

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Registered trials

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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.