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10:58
Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Published on: July 25, 2013
A direct comparison of protein interaction confidence assignment schemes
Silpa Suthram1, Tomer Shlomi, Eytan Ruppin
1Department of Bioengineering, University of California, San Diego, CA 92093, USA. ssuthram@ucsd.edu
BMC Bioinformatics
|July 29, 2006
Summary
Evaluating protein-protein interaction confidence scores is crucial due to high false positive rates. The Deng et al. method demonstrates superior performance in identifying reliable protein interactions across multiple assessment metrics.
Area of Science:
- Systems Biology
- Bioinformatics
- Computational Biology
Background:
- High-throughput technologies generate extensive protein-protein interaction (PPI) networks.
- Yeast two-hybrid and similar methods often yield high false positive rates.
- Confidence scoring methods are essential for validating PPI data.
Purpose of the Study:
- To rigorously compare and assess the performance of various PPI confidence scoring methods.
- To identify the most effective scheme for assigning confidence to protein interactions.
Main Methods:
- Assessed confidence score correlation with protein functional similarity, expression patterns, and sequence conservation.
- Utilized a novel Signal-to-Noise Ratio metric for protein complex detection.
- Compared seven distinct confidence assignment schemes, including Bader et al., Deane et al., Deng et al., Sharan et al., and Qi et al.
Main Results:
- Confidence scores correlate with protein functional, expression, and conservation similarities.
- The Signal-to-Noise Ratio metric effectively assesses method performance.
- Performance varied across schemes and assessment metrics.
Conclusions:
- The Deng et al. confidence assignment scheme performed best overall, excelling in three out of four metrics.
- Employing any probability-based confidence assignment scheme is superior to assuming all interactions are equally valid.
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