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However, in essence it is a network which consists of nodes and edges, which is better visualized as a graph.
Once the transport system is visualized as a graph, various network properties can be evaluated based on the relationships between the network elements.
PPIs can be visualized as a graph with proteins composing the nodes, and interactions composing the edges (the graphical interactions).
The outcome of this model is visualized as a graph.
The adjacency matrix was also visualized as a graph and the number of topological properties of this graph examined.
The results were visualized as a graph, such that genes form the nodes, which are joined by an edge if the value of correlation between them is higher than selected threshold.
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The protein space can be visualized as a graph-like structure, where nodes represent proteins and a significant alignment is saved as an edge between two nodes.
From the results of 10 independent runs with 100.000 iterations each and a burn-in period of 100.000 a 50% majority rule consensus tree was computed and visualized as a dot graph.
This could then be visualized as a line graph.
The model can be visualized as a bipartite graph.
This can be formalized as a classical mathematical relationship visualized as an undirected graph.
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