چكيده به لاتين
Graph data monitoring discussion which has been regarded in recent years represents a novel area of research in the field of quality engineering. Complex networks such as social network, information network, technological network, and biological network are collected using graph data in which entities play the role of nodes and edges are formed between each pair of nodes according to their interests, tendencies, purposes, and benefits. Network analysis has led to detect network anomalies which also can effectively help an organization or any set that includes a network of members and interactions.
In this research, given the importance of biological networks in living systems at the molecular level, a network of protein-protein interactions was studied during the cancerous cells progression. Thus, the protein-protein interaction networks during cancer condition in bone was modeled by exponentially random graph model in which we summarized each network data in the form of graphs, with proteins as nodes and interactions as edges. Then, by considering the interactions in protein interactions network as a process over time, we applied the likelihood ratio test to detect out-of-control state. Simulation result shows that proposed method has a satisfactory performance in the early detection of bone cancer.
