  In this paper, we compared cancerous and normal cell according to their
protein-protein interaction network. Cancer is one of the complicated diseases
and experimental investigations have been showed that protein interactions have
an important role in the growth of cancer. We calculated some graph related
parameters such as Number of Vertices, Number of Edges, Closeness, Graph
Diameter, Graph Radius, Index of Aggregation, Connectivity, Number of Edges
divided by the Number of Vertices, Degree, Cluster Coefficient, Subgraph
Centrality, and Betweenness. Furthermore, the number of motifs and hubs in
these networks have been measured. In this paper bone, breast, colon, kidney
and liver benchmark datasets have been used for experiments. The experimental
results show that Graph Degree Mean, Subgraph Centrality, Betweenness, and Hubs
have higher values in the cancer cells and can be used as a measure to
distinguish between normal and cancerous networks. The cancerous tissues of the
five studied samples are denser in the interaction networks.
