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Future parcellation can easily be based on connectivity to already known tracts (e.g., SLF).
Networks were then generated based on connectivity.
Focus gene networks were algorithmically generated based on connectivity.
Gene networks were algorithmically generated based on connectivity.
Many real complexes with different connectivity level in protein interaction network can be predicted based on connectivity number.
The post-processing step filters or adds nodes based on connectivity criteria.
We algorithmically constructed networks containing the identified genes based on connectivity and known relationships among molecules.
Networks containing miRNA targets were algorithmically constructed based on connectivity and the known relationships among proteins.
The following theorem allows the identification of all cut edges based on the connectivity matrix P G. Theorem 1.
Phase I. We start by identifying, based on the connectivity matrix M, vertices from G direct with low degree, together with edges incident to them.
The network representation of the results (Fig. 1), based on this connectivity matrix, was generated using U cinet® software (Borgatti et al. 2002).
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