Network cartographs for interpretable visualizations

Nat Comput Sci 2, pages 84–89 (2022)
PMID: https://doi.org/10.1038/s43588-022-00199-z
Nat Comput Sci 2, pages 84–89 (2022)
PMID: https://doi.org/10.1038/s43588-022-00199-z

Networks offer an intuitive visual representation of complex systems. Important network characteristics can often be recognized by eye and, in turn, patterns that stand out visually often have a meaningful interpretation. In conventional network layout algorithms, however, the precise determinants of a node’s position within a layout are difficult to decipher and to control. Here we propose an approach for directly encoding arbitrary structural or functional network characteristics into node positions. We introduce a series of two- and three-dimensional layouts, benchmark their efficiency for model networks, and demonstrate their power for elucidating structure-to-function relationships in large-scale biological networks.

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