ArticleNature biotechnology2005
Effect of sampling on topology predictions of protein-protein interaction networks.
Article in Nature biotechnology, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 115 papers.
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Who cites it
115 citing papers in PubMed.
- The signed two-space proximity model for learning representations in protein-protein interaction networks.Bioinformatics (Oxford, England) · 2025Article
- Recent progress and future challenges in structure-based protein-protein interaction prediction.Molecular therapy : the journal of the American Society of Gene Therapy · 2025Review
- Challenges and opportunities for digital twins in precision medicine from a complex systems perspective.NPJ digital medicine · 2025Review
- Simplicity within biological complexity.Bioinformatics advances · 2025Article
- Emergence of power law distributions in protein-protein interaction networks through study bias.eLife · 2024Article
- Inference of single-cell network using mutual information for scRNA-seq data analysis.BMC bioinformatics · 2024Article
- Folding and Binding Kinetics of the Tandem of SH2 Domains from SHP2.International journal of molecular sciences · 2024Article
- The probability of edge existence due to node degree: a baseline for network-based predictions.GigaScience · 2024Article
- SWEET: a single-sample network inference method for deciphering individual features in disease.Briefings in bioinformatics · 2023Article
- The probability of edge existence due to node degree: a baseline for network-based predictions.bioRxiv : the preprint server for biology · 2023Article
- Long-distance dependency combined multi-hop graph neural networks for protein-protein interactions prediction.BMC bioinformatics · 2022Article
- SANA: cross-species prediction of Gene Ontology GO annotations via topological network alignment.NPJ systems biology and applications · 2022Article
- Melanopsin (Opn4) is an oncogene in cutaneous melanoma.Communications biology · 2022Article
- Overview of methods for characterization and visualization of a protein-protein interaction network in a multi-omics integration context.Frontiers in molecular biosciences · 2022Review
- Link Prediction through Deep Generative Model.iScience · 2020Article
- Graph-based prediction of Protein-protein interactions with attributed signed graph embedding.BMC bioinformatics · 2020Article
- Abasy Atlas v2.2: The most comprehensive and up-to-date inventory of meta-curated, historical, bacterial regulatory networks, their completeness and system-level characterization.Computational and structural biotechnology journal · 2020Article
- Volume explored by a branching random walk on general graphs.Scientific reports · 2019Article
- Evolutionary constraints on the complexity of genetic regulatory networks allow predictions of the total number of genetic interactions.Scientific reports · 2019Article
- Article
55 more citing papers are in PubMed but not listed here.
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5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Currently available protein-protein interaction (PPI) network or 'interactome' maps, obtained with the yeast two-hybrid (Y2H) assay or by co-affinity purification followed by mass spectrometry (co-AP/MS), only cover a fraction of the complete PPI networks. These partial networks display scale-free topologies--most proteins participate in only a few interactions whereas a few proteins have many interaction partners. Here we analyze whether the scale-free topologies of the partial networks obtained from Y2H assays can be used to accurately infer the topology of complete interactomes. We generated four theoretical interaction networks of different topologies (random, exponential, power law, truncated normal). Partial sampling of these networks resulted in sub-networks with topological characteristics that were virtually indistinguishable from those of currently available Y2H-derived partial interactome maps. We conclude that given the current limited coverage levels, the observed scale-free topology of existing interactome maps cannot be confidently extrapolated to complete interactomes.
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