Table 4 Results on real networks from neurodegenerative dataset used in our experiment, the disease name, unique number of genes in the result set, number of embeddings, \(\mathcal {F}_{2}\) measure and the running time
From: ProMotE: an efficient algorithm for counting independent motifs in uncertain network topologies
Disease | Unique Genes | Embeddings | \(\mathcal {F}_{2}\) | Time (s) |
|---|---|---|---|---|
AD | 67 | 228 | 87.2108 | 1984.74 |
HD | 67 | 228 | 87.2108 | 2006.99 |
PD | 70 | 234 | 88.6849 | 2019.60 |