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The current implementation converts BCML files into GraphML, a widely used format for graph representation.
For graph representation, the number of clusters p is set to 5, assuming that there are 5 different tissues in each image on average.
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Fig. 6 An example of graph representation for our Twitter datasets.
Figure 6 shows an example where actor A retweeted 3 tweets of actor B, whereas the actor C retweeted 2 tweets of the actor A. Fig. 6 An example of graph representation for our Twitter dataset.
The memory usage of PAGAN is dominated by the dynamic programming matrix and, due to a more complex data structure needed for the graph representation, the requirements are, for example, somewhat higher than that of MAFFT with a comparable alignment strategy.
c For better graph representation, we omit the graphs for the uplink.
This supplementary information is not needed for the graph representation of the endocrine network and therefore also the node can be removed.
In the Bayesian hierarchical approach, item and person parameters are estimated using a Markov Chain Monte Carlo procedure, in which cohort-specific item parameters are considered level-1 parameters randomly distributed around overall mean item parameters at level 2. See Fig. 1 for a graph representation of the hierarchical structure of both item and person parameters across cohorts.
Second, (mathsf {DMST}) is an algorithm which traverses the minimum spanning tree T constructed for the edge-weighted undirected graph representation for (Q).
We implemented two algorithms for the planar graph representation.
Similar results were found also for a bipartite graph representation including both reactions and metabolites as nodes (additional file 2, section 1.2).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com