Abstract
Background: Protein complexes are responsible for most of vital biological processes within the cell. Understanding the machinery behind these biological processes requires detection and analysis of complexes and their constituent proteins. Recent biological experiments on yeast by Gavin et al. (2006) revealed that proteins within a complex are organized into two parts: core and attachment. Based on these insights, we recently [2] proposed a new algorithm called MCL-CA, based on Markov clustering coupled with core-attachment based refinement, to detect protein complexes from yeast protein-protein interaction networks (PPI). We showed that the core-attachment based refinement significantly improved the accuracies of predicted complexes when matched with manually-curated yeast complexes. However, MCL-CA was still prone to noise (false positives) in the interaction datasets.
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