Detection of spreader nodes and ranking of interacting edges in Human-SARS-CoV protein interaction network

Sovan Saha; Piyali Chatterjee; Subhadip Basu; Mita Nasipuri

By analyzing the above facts, it has been felt that there is a pressing need to understand the proper way of disease transmission from SARS-CoV-2 PPIN to human PPIN [16] - [18] . But since SARS-CoV-2 PPIN is still not available, SARS-CoV PPIN is considered for this research study. As discussed earlier, due to its high genetic similarity with SARS-CoV-2, the same will help in better understanding of SARS-CoV-2 PPIN. In the proposed methodology, at first SARS-CoV-Human PPIN (up to level-2) is formed from the collected datasets [25] - [27] . Once it is formed, spreader nodes are identified in each of SARS-CoV proteins, its level-1 and level-2 of human network by the application of a new network attribute i.e. spreadability index which is a combination of three terminologies: 1) edge ratio [28] 2) neighborhood density [28] and 3) node weight [29] . The detected spreader nodes are also validated by the existing SIS epidemic disease model [30] . Then the edges connecting two spreader nodes are ranked based on the average of spreadability index of spreader nodes themselves to access to the spreading ability of the corresponding edge. The ranked edges thus highlight the path of entire disease propagation from SARS-CoV to human level-1 and then from human level-1 to human level-2 proteins.