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One way to define hubs is to use the mutual connectivity properties of high degree nodes in protein interaction networks.
To define hubs using a mutual connectivity criterion, one may therefore construct a subgraph connectivity measure in the following way.
Therefore, one way to define hub proteins could involve identifying the set of high-degree proteins that has significantly lower mutual connectivity than proteins that do not lie in this set.
It would appear that mutual connectivity between immune cells is essential to integrated, collective immune function.
The features most reliably associated with a particular stimulus category will most likely have the strongest mutual connectivity.
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Interesting properties emerge from this kind of analysis, in particular, the mutual connectivities between immune cells and between the immune system and the body.
The ability of neurons to synchronize their spiking activity depends on their mutual synaptic connectivity and their intrinsic properties.
They favour alliances and unions, mutual support and connectivity, and they reject introversion and isolation.
In essence the GSVD algorithm allows the reordering of the two experimental matrices A (control animals) and B (PCP-treated animals) with the aim of discovering a new node (metabolite) ordering that reveals clusters of nodes that exhibit strong connectivity (mutual weights) in one network but not the other.
Because of the strong mutual influences between neuronal connectivity and activity, and the development of connectivity, already shown at network level (le Feber et al. 2009, 2010), further electrophysiological experiments may functionally validate the effects of OXA on the network activity.
They require a mechanism for professional connectivity and mutual support.
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