Real-world network datasets often contain a wealth of complex topological information. In the face of these data, researchers often employ methods to extract reduced networks containing the most important structures or pathways, sometimes known as ‘skeletons’ or ‘backbones’. Numerous such methods have been developed. Yet data are often noisy or incomplete, with unknown numbers of missing or spu...
