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In this review, we summarize the different approaches available for engineering neural networks treated analogously to a mathematical graph consisting of cell bodies and axons as nodes and edges, respectively.
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A mathematical description of a network is a directed graph consisting of vertices and directed arcs connecting them.
Their approach is to consider a general graph consisting of various nodes and the links between them.
For example, the graph K5 is the graph consisting of 5 nodes, each joined to the other by an arc.
Our method uses a heterogeneous graph consisting of three sub-graphs connected to each other.
The Pareto graph consists of two groups.
The extracted graph consists of 726,467 vertices.
The resulting graph consists of 11,790 nodes and 44,624 edges.
The graph consisted of vertices that corresponded to TM positions.
The obtained graph consisted of 18,600 nodes and 1,640,707 edges.
This graph consisted of 8 sub-graphs, with the largest connected component having 76 pathways and 396 GOBP terms.
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