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Updated: Jul 17, 2026
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Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay (PCA) in Living Cells
Published on: March 3, 2015
Comparison of human protein-protein interaction maps
Matthias E Futschik1, Gautam Chaurasia, Hanspeter Herzel
1Institute for Theoretical Biology, Charité, Humboldt-Universität, 10115 Berlin, Germany. m.futschik@biologie.hu-berlin.de
Bioinformatics (Oxford, England)
|January 24, 2007
Summary
Comparing eight human interactome maps reveals limited overlap and significant biases. These findings are crucial for future integration of protein interaction data and understanding cellular mechanisms.
Area of Science:
- Molecular Biology
- Systems Biology
- Bioinformatics
Background:
- Large-scale protein-protein interaction (PPI) mapping is essential for understanding cellular mechanisms.
- Focus has shifted to mapping the human interactome, presenting a significant challenge.
- Several large-scale human PPI maps have been published, necessitating quality assessment.
Purpose of the Study:
- To conduct a comparative analysis of existing large-scale human protein interaction maps.
- To assess the quality and identify biases in current human interactome datasets.
- To inform future efforts in assembling a comprehensive human interactome network.
Main Methods:
- Comparative analysis of eight large-scale human PPI maps.
- Inclusion of over 10,000 unique proteins and 57,000 interactions.
- Evaluation of maps derived from literature search, orthology, and yeast-two-hybrid assays.
Main Results:
- A small, statistically significant overlap was found among the analyzed human interactome maps.
- Clear indications of considerable selection and detection biases present in all maps.
- The study highlights the need to account for biases in future interactome assembly.
Conclusions:
- Current large-scale human PPI maps exhibit limited agreement and inherent biases.
- The findings underscore the importance of critical evaluation and bias correction for accurate interactome representation.
- An integrated human interaction network, UniHI, is publicly available for research.
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