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Table 1 STM algorithm

From: A novel functional module detection algorithm for protein-protein interaction networks

Algorithm 1: STM(G)
1: V: set of nodes in Graph G
2: F(c): Transduction behavior function
3: S(v, w): arrived signal from node v to node w
4: C: the list of final clusters
5: PreClusters: the list of preliminary clusters
6: for each node pair(v, w) v, w V, vw do
7:    distance(v, w) ← the shortest path length from node v to node w
8:    set parameter c in function as F(c) as distance(v, w)
9:    signal(v, w) ← S ( v w ) = d ( v ) i P ( v , w ) d ( i ) F ( c ) MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaacqWGtbWucqGGOaakcqWG2bGDcqGHsgIRcqWG3bWDcqGGPaqkcqGH9aqpdaWcaaqaaiabdsgaKjabcIcaOiabdAha2jabcMcaPaqaamaarababaGaemizaqMaeiikaGIaemyAaKMaeiykaKcaleaacqWGPbqAcqGHiiIZcqWGqbaucqGGOaakcqWG2bGDcqGGSaalcqWG3bWDcqGGPaqkaeqaniabg+GivdaaaOGaemOrayKaeiikaGIaem4yamMaeiykaKcaaa@4DCA@
10: end for
11: for each node v V do
12:       v. representative ← select the best scored node w for node v
13:       if cluster_w == null then
14:          make cluster_w
15:          cluster_w.add(v)
16:          PreClusters.add(cluster_w)
17:       else
18:          cluster_w.add(v)
19:       end if
20: end for
21: CMerge(PreClusters)