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Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
Published on: July 14, 2015
The effects of incomplete protein interaction data on structural and evolutionary inferences
Eric de Silva1, Thomas Thorne, Piers Ingram
1Theoretical Genomics Group, Centre for Bioinformatics, Division of Molecular Biosciences, Imperial College London, London, UK. e.desilva@imperial.ac.uk <e.desilva@imperial.ac.uk>
Protein interaction networks are incomplete, leading to biased analyses. Researchers must account for network sampling properties to accurately understand biological systems and avoid misinterpretations.
Area of Science:
- Systems Biology
- Bioinformatics
- Network Science
Background:
- Current protein interaction network datasets represent only partial coverage of an organism's proteome.
- Previous analyses have often overlooked the potential biases introduced by using incomplete network data.
Purpose of the Study:
- To demonstrate the necessity of explicitly considering network sampling properties in all analyses.
- To evaluate the impact of incomplete network data on network statistics, network motifs, and functional/evolutionary inferences.
Main Methods:
- Analysis of the yeast protein interaction network using various network statistics.
- Simulation of random and non-random sampling schemes to assess data incompleteness.
- Evaluation of effects independent of inherent noise in protein interaction data.
Main Results:
- Incomplete network data significantly affects network properties, particularly network motifs.
- The observed effects are robust and independent of inherent noise in protein interaction data.
- Bias in network analysis is almost unavoidable when using small, partial datasets.
Conclusions:
- Ignoring the incomplete nature of protein interaction network data leads to inevitable bias.
- Previous studies relying on partial network data may require reassessment.
- Accurate understanding of biological systems necessitates addressing network incompleteness from the start.
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