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Through 3D animated pictorially representations of the state and flow of information in the network, a better understanding of network functionality is achieved.
Experimental results show that this approach can be very useful for a better understanding of network traffic data, making it easier to search for evidence of attacks or anomalous behaviour in a network environment.
Therefore, identifying different network motif types is the first step towards a better understanding of network biology at a system level.
More generally this might eventually contribute to a better understanding of network effects relating to learning, development and degeneration (Fair et al., 2008; Seeley et al., 2009; Dayan and Cohen, 2011).
More generally this might eventually contribute to a better understanding of network effects relating to learning, development and degeneration (Dayan and Cohen, Neuron, 2011; Fair et al, PNAS, 2007; Seeley et al, Neuron., 2009).
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The quantitative 3D reconstructions of synapses will enable the comparison of structural and functional aspects of signal transduction thus leading to a better understanding of networks in the developing neocortex.
A better understanding of diseasome network, such as protein protein interaction network, might lead to the identification of disease biomarkers, elucidation of underlying mechanisms and new drug discovery.
This coarse network structure contributes to a better understanding of the network behavior, and – even more importantly – allows the clear identification of the fragile node in the network.
These improvements to the recording conditions enable detailed studies of neurons under more realistic conditions of network activity, which are essential for a better understanding of neuronal network operation.
The crucial point is that the hierarchical description reveals the structuring principle inherent in the T-invariants, which may contribute to a better understanding of the network behavior.
Liang et al. obtained a better understanding of the network pharmacology analysis of the herbal formula Liuwei Dihuang [ 3].
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