Identification of Essential Cancer Protein in PPI Network Using Graph-Based Approach

Identifying essential cancer proteins is critical in cancer research, as targeting these proteins can lead to effective cancer treatments. The proposed method is primarily intended to design a novel approach for identifying essential cancer proteins in the PPI network using a graph-based method. This method is used to find the shortest path on a biological network. The network is analysed using centrality measures, and a threshold value of betweenness centrality filters out nonessential proteins from the list of candidate proteins. The proposed graph-based method revealed that 50 essential proteins are selected from the list of proteins. Finally, the permutation test is performed to validate the findings. The proposed graph-based method identifies disease-related proteins in various contexts by performing common gene identification, PPI network construction, network analysis and validation. This method can be adapted and applied to different cancer types by adjusting the gene selection criteria, network construction methods, and validation stratcgies.