ArticlePloS one2012
Simulated evolution of protein-protein interaction networks with realistic topology.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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.
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.
Who cites it
14 citing papers in PubMed.
- Protein Stability, Turnover Kinetics, and Abundance Constrain the Scaling of Protein Interaction Networks.bioRxiv : the preprint server for biology · 2026Article
- Circulating causal protein networks linked to future risk of myocardial infarction.Nature communications · 2025Article
- Single-molecule reaction-diffusion.Biophysical journal · 2025Article
- The Bootstrap Model of Prebiotic Networks of Proteins and Nucleic Acids.Life (Basel, Switzerland) · 2022Article
- Asymmetry between Activators and Deactivators in Functional Protein Networks.Scientific reports · 2020Article
- Towards a Dynamic Interaction Network of Life to unify and expand the evolutionary theory.BMC biology · 2018Review
- Hidden long evolutionary memory in a model biochemical network.Physical review. E · 2018Article
- Evolutionary analysis and interaction prediction for protein-protein interaction network in geometric space.PloS one · 2017Article
- Structural Perspectives on the Evolutionary Expansion of Unique Protein-Protein Binding Sites.Biophysical journal · 2015Article
- Merging molecular mechanism and evolution: theory and computation at the interface of biophysics and evolutionary population genetics.Current opinion in structural biology · 2014Review
- A maximum entropy framework for nonexponential distributions.Proceedings of the National Academy of Sciences of the United States of America · 2013Article
- Computational Prediction of Protein-Protein Interaction Networks: Algo-rithms and Resources.Current genomics · 2013Article
- Experimental evolution of protein-protein interaction networks.The Biochemical journal · 2013Review
- Evolutionary Model Selection and Parameter Estimation for Protein-Protein Interaction Network Based on Differential Evolution Algorithm.IEEE/ACM transactions on computational biology and bioinformaticsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
We model the evolution of eukaryotic protein-protein interaction (PPI) networks. In our model, PPI networks evolve by two known biological mechanisms: (1) Gene duplication, which is followed by rapid diversification of duplicate interactions. (2) Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the target protein's neighborhood. We find good agreement of the model on 10 different network properties compared to high-confidence experimental PPI networks in yeast, fruit flies, and humans. Key findings are: (1) PPI networks evolve modular structures, with no need to invoke particular selection pressures. (2) Proteins in cells have on average about 6 degrees of separation, similar to some social networks, such as human-communication and actor networks. (3) Unlike social networks, which have a shrinking diameter (degree of maximum separation) over time, PPI networks are predicted to grow in diameter. (4) The model indicates that evolutionarily old proteins should have higher connectivities and be more centrally embedded in their networks. This suggests a way in which present-day proteomics data could provide insights into biological evolution.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.