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

Sovan Saha; Piyali Chatterjee; Subhadip Basu; Mita Nasipuri

In the proposed methodology, Protein-protein interaction network (PPIN) has been used as the central component in identification of spreader nodes in SARS-CoV. PPIN has been found to be very effective module for protein function determination [16] - [18] as well as in the identification of central/essential or key spreader nodes in the network [19] - [23] . Compactness of the network and its transmission capability is estimated using centrality analysis. Anthonisse et al. [23] proposed a new centrality named as Betweenness Centrality (BC) . BC is actually defined as the measure of impact of a particular node over the transmission between every pair of nodes with a consideration that this transmission is always executed over the shortest path between them. It is defined as: ) where ( , ) is the total number of shortest paths from node to node and ( , , ) is the number of those paths that pass through . Another centrality, closeness centrality (CC), was defined by Sabidussi et al. [24] . It is actually a procedure for detecting nodes having efficient transmission capability within a network. Nodes which have high closeness centrality value are considered to have the shortest distance to all available nodes in the network. It can be mathematically expressed as: