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Identifying candidate genes/proteins involved in human disease specific molecular pathways or networks has been a primary focus of biomedical research. Although node ranking and graph clustering methods can help identify localized topological properties in a network, it remains unclear how the results should be interpreted in biological functional context in systems-level. In complex biomolecular interaction networks, biomolecular entities may not have absolute ranks or clear cluster boundary among them. We presented ant colony optimization reordering (ACOR) method to examine emerging network properties. The task of reordering nodes is represented as the problem of finding optimal density distribution of ldquoant colonyrdquo on all nodes of the network. We applied ACOR method to re-analyze a yeast protein-protein interaction (PPI) network annotated with functional information (i.e., lethality), which revealed intriguing systems-level functional features.