ArticleGenome biology2007
Coverage and error models of protein-protein interaction data by directed graph analysis.
Article in Genome biology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
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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.
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Who cites it
18 citing papers in PubMed.
- Overview of methods for characterization and visualization of a protein-protein interaction network in a multi-omics integration context.Frontiers in molecular biosciences · 2022Review
- Integrated network analysis reveals new genes suggesting COVID-19 chronic effects and treatment.Briefings in bioinformatics · 2021Article
- Protein-Protein Interactions in Virus-Host Systems.Frontiers in microbiology · 2017Review
- Going the distance for protein function prediction: a new distance metric for protein interaction networks.PloS one · 2013Article
- Diversity in genetic in vivo methods for protein-protein interaction studies: from the yeast two-hybrid system to the mammalian split-luciferase system.Microbiology and molecular biology reviews : MMBR · 2012Review
- Review
- Multiple genetic interaction experiments provide complementary information useful for gene function prediction.PLoS computational biology · 2012Article
- Towards a rigorous network of protein-protein interactions of the model sulfate reducer Desulfovibrio vulgaris Hildenborough.PloS one · 2011Article
- From evidence to inference: probing the evolution of protein interaction networks.HFSP journal · 2009Article
- Triangle network motifs predict complexes by complementing high-error interactomes with structural information.BMC bioinformatics · 2009Article
- A general pipeline for quality and statistical assessment of protein interaction data using R and Bioconductor.Nature protocols · 2009Article
- High throughput interaction data reveals degree conservation of hub proteins.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2009Article
- An experimentally derived confidence score for binary protein-protein interactions.Nature methods · 2009Article
- Protein interaction predictions from diverse sources.Drug discovery today · 2008Review
- Modeling synthetic lethality.Genome biology · 2008Article
- A portrait of copy-number polymorphism in Drosophila melanogaster.Proceedings of the National Academy of Sciences of the United States of America · 2007Article
- Making the most of high-throughput protein-interaction data.Genome biology · 2007Review
- Mapping protein-protein interactions by mass spectrometry.Mass spectrometry reviewsReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Using a directed graph model for bait to prey systems and a multinomial error model, we assessed the error statistics in all published large-scale datasets for Saccharomyces cerevisiae and characterized them by three traits: the set of tested interactions, artifacts that lead to false-positive or false-negative observations, and estimates of the stochastic error rates that affect the data. These traits provide a prerequisite for the estimation of the protein interactome and its modules.
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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.