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All significance values based on network measures were calculated using QAP.
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The prioritization was based on network centrality measures and these proteins found at the centre of gravity of the proteome network.
One can use classifiers that, based on network features and measures, classify each tentative link as existing or not [18]; one may also resort to collective classification over the whole set of possible links [7].
Some researches are based on network topology and centrality measures [9].
Consequently, these algorithms treat all networks effectively as complete graphs, and are not directly amenable to complexity bounds based on network structure, such as measured by treewidth, that are well known in the finite-domain case.
To study the relative importance and associations among different factors, we constructed causal maps and used centrality measures based on network analysis to identify the dominant discourse.
Modules that are significantly enriched with host dependency factors (HDFs) and/or host restriction factors (HRFs) are then filtered based on network topology and semantic similarity measures.
The experimental results show that the integration of network topology and gene expression increased the predictability of essential proteins in comparison with those centrality measures only based on network topological features.
With the integration of network topology and gene expression, the same group of researchers proposes a new method called PeC [ 23]which increases the predictability of essential proteins in comparison with those centrality measures only based on network topological features.
In terms of network structure, we built a biography network [27] in which we estimated PageRank, a measure of node centrality based on network connectivity [20, 21].
The method developed by Nabieva E. et al. [ 28] is based on network flow and integrates both network topology and locality measures.
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