Several algorithms, based on edge-betweenness centrality [ 28], on shortest path distances within a network, on the Statistical-Algorithmic Method for Bicluster Analysis (SAMBA) [ 29] or on the approximation mapping of network nodes into Euclidean space followed by fuzzy c-means clustering [ 30] were developed to identify dense sub-graphs and functional modules within the PPI networks.
Linear regression also has in our context a simple communication-theoretic interpretation: in the high SINR regime, linear functions approximate well the Shannon capacity formula, and y becomes simply the best approximation of the network throughput as a optimal weighted sum of the individual Shannon capacity estimates.
Nevertheless, the assumed unit disk graph model is only a rough approximation of the network connectivity.
By exploiting principles borrowed from compressed sensing, we show that the proposed technique can achieve a good approximation of the network data at the sink node with only a few packets received and that this approximation gets progressively better as the number of received packets increases.
Thus, there is no obvious relationship between the BA model and the CPBA approximation of a network.
Although automatic tools do provide a first approximation of the network structure, human analysis remains necessary for curating all the relevant information.
The approximation of the network estimate for a single comparison by the evidence of a subnet and the visualisation of the decomposition into independent paths provide the applicability of a graphical validation instrument that is known from classical meta-analysis.
Although (6) is a random variable, in the deterministic ODE approximation of the network, as t′- t→0, it approaches v j, the reaction flux of j at time t.
The inner optimization process allows us to obtain the product yield, x5(t final ), given a certain u(t), taking into account a valid approximation of the network dynamics over the simulation time.
Below we show that the new PG generation approach in combination with the proposed ranking scheme may already deliver a valuable approximation of the network itself but can often be further improved by TR techniques.
