Table 1 Major steps of GANE

Input: Graph G = (V, E), GO property matrix O, vector representation dimension d, threshold value θ

Output: A set of discovered protein complexes

Description:

Constructing a protein attribute affinity matrix S∈R^n×n

Generating vector representation for each protein φ∈R^d

Constructing a weighted adjacency matrix W

Initializing Alternative_core, Seed_core, ComplexSet to be \( \varnothing \)

Generating maximal cliques and put them into Alternative_core

While \(\textit {Alternative\_core}\ne \varnothing \):

DescendSort(Alternative_core) by density_score

Alternative_core=Alternative_core−Clique₁

Seed_core=Seed_core+Clique₁

Pruning and updating remaining cliques in Alternative_core

End while

For core core_i in Seed_core

finding the set of its attachments Att_i

ComplexSet=ComplexSet+ core_i∪Att_i

End for

Return ComplexSet