Peer-to-Peer Experimentation in Protein Structure Prediction: an Architecture, Experiment and Initial Results

Peer-to-peer approaches offer some direct solutions to modularity and scaling properties in large scale distributed systems but their role in supporting precise experimental analysis in bioinformatics has not been explored closely in practical settings. We describe a method by which precision in experimental process can be maintained within a peer-to-peer architecture and show how this can support experiments. As an example we show how our system is used to analyse real data of relevance to the structural bioinformatics community. Comparative models of yeast protein structures from three individual resources were analysed for consistency between them. We created a new resource containing only model fragments supported by agreement between the methods. Resources of this kind provide small sets of likely accurate predictions for non-expert users and are of interest in applied bioinformatics research.