Briefly, the shortest path between two given nodes in a network is the minimum number of edges that need to be traversed to get from one node to the other; the diameter of a network is the maximum length among all shortest paths between any two nodes in the network.
Once a calculated distance between two given times has been obtained, additional information is required to locate the train within a network.
AlignNemo [ 18] is one of such recent efforts, which detects network clusters on an alignment network of two given PPI networks.
But despite the current ubiquity of networks, it hasn't always been obvious to science that the connections between elements in any given network are, often, as interesting as the isolated network elements themselves, or that understanding one kind of network might shed light on others.
The answer is: by forming giving networks.
The total number of n edges common between two networks is given by n = G 1 ∩ G 2. The joint number of m edges of two subnetworks S for a GO term t is given by m = S t (G 1 e ∪ G 2 e ).
The amount of energy for a single hop transfer between the given two network nodes can be calculated by a trivial function given in Equation (1): {mathrm{WE}}_{ij}=Eleft({V}_i, {V}_jright) (1).
Network lifetime results for the number of sinks (sink count) between two and eight are given in Fig. 3. Our MSMA algorithm gives a better network lifetime compared to other schemes for all values of sink count.
Summarily, comparison between two network architectures is given in Table 1.
In this framework, in a given pair of PPI networks, the alignment score between two PPI networks is calculated based on matches, mismatches, and duplications.
