Network topological reordering revealing systemic patterns in yeast protein interaction networks.
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 "ant colony" 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.
Wu
Xiaogang
X
School of Informatics, Indiana University, Indianapolis, IN 46202, USA. wu33@iupui.edu
Pandey
Ragini
R
Chen
Jake Yue
JY
D001698:Biomedical Engineering; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D025941:Protein Interaction Mapping / Q000706:statistics & numerical data*; D012441:Saccharomyces cerevisiae / Q000378:metabolism; D029701:Saccharomyces cerevisiae Proteins / Q000737:chemistry / Q000378:metabolism*; D049490:Systems Biology
D029701:Saccharomyces cerevisiae Proteins