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*M ACN
> 9 | max flow min cut : applications in clusterin > Flashcards
9 | max flow min cut : applications in clusterin Flashcards
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*M ACN
(14 decks)
R stuff
0 | refreshing basics
1 | intro to networks; DFS and BFS
2 | articulation point / bridge and their importance
3 | network properties and types
4 | centrality measures : distance-based, eigenvalue-based
5 | network randomization and random network models : empirical p-value
6 | subnetworks and their properties : network motifs
7 | clustering and networks I : data clustering and cluster quality measures
8 | clustering and networks II : network clustering (cuts) and cluster quality measures
9 | max flow min cut : applications in clusterin
10 | network alignment : approaches and applications
11 | – network representation of data / single cell RNA seq : geometric network representation
12 | advanced topics – machine learning and networks (graph neural networks)
