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Modeling multi-scale data via a network of networks
Prediction of node and graph labels are prominent network science tasks.
Data-driven biological network alignment that uses topological, sequence, and functional information
Existing NA assumes that it is topological similarity (isomorphic-like matching) between network regions that corresponds to the regions' functional relatedness.
Data-driven network alignment
A likely reason is that they assume it is topologically similar nodes that are functionally related.
Pairwise versus multiple network alignment
Just as the recent trend in the NA field, we also focus on global NA, which can be pairwise (PNA) and multiple (MNA).
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