LARGE-SCALE COMPLEX NETWORK ANALYSIS TO INVESTIGATE ASSOCIATIONS OF DISORDERED PROTEINS AND SCALE-FREE NETWORK
Keywords:
Protein-protein interaction network, disordered protein, scale-free network, degree distribution, power-law formAbstract
In biomedical engineering studies, a protein-protein interaction network is widely used to identify biological processes and characterize associations among proteins. Typically, its structure forms a scale-free network which contains a few hub proteins and a lot of low-degree proteins. Thus, its degree distribution follows the power-law distribution. Investigating such a protein that might affect this structure may reveal an important protein for the whole network. In this research, we investigated disordered proteins whose removal results in a non-scale-free structure that may cause severe diseases like cancers. Later, a simple measure to identify these proteins was developed as an alternative method avoiding fitting a power-law distribution. A high performance for identifying disordered proteins was achieved by using the area under the ROC curve value greater than 0.9. In addition, the measure yielded a superior performance to the random selection procedure.
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