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According to the characters of the network, network survivability is generally use as survivability measurement as the basis and establishes the survivability analysis model based on the probability theory and graph theory, etc.
62 To gain maximal insights from a biological network that has been reconstructed as described above, systematic analysis of the network (network interrogation) is essential.
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In particular, studies of protein-interaction networks have revealed complex relationships between vertex degree (number of neighbors in the network), network modularity (organization of the network into connected subnetworks), gene essentiality, gene pleiotropy, and so on.
While most of the known biology is represented in the visible backbone of the networks, network computations can be performed using a downstream (hidden) layer of RNA abundance of genes regulated by the nodes in the backbone.
To explain the ontology of the functional network, Network Ontology Analysis (NOA) which applied the categories of Gene Ontology to network analysis [ 24] would be employed.
For example, functional connectivity of the top network (network #1) revealed a strong over-representation of NF-kB (Figure 3).
Topological properties of the co-occurrence network (positive network) of 46 major CAG families and 40 prevalent phylogenetic orders.
Comparison of the functional linkage network with previously published networks.
They also leave no trace on the phone, or on the network of the network provider, that communications have been monitored.
When it approaches the limit of the network, the network performance parameters are achieved.
The hidden layer represents the main part of the network and covers the network of neurons.
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