def find_activations(graph: BELGraph):
for u, v, key, data in graph.edges(keys=True, data=True):<EOL><INDENT>if u != v:<EOL><INDENT>continue<EOL><DEDENT>bel = graph.edge_to_bel(u, v, data)<EOL>line = data.get(LINE)<EOL>if line is None:<EOL><INDENT>continue  <EOL><DEDENT>elif has_protein_modification_increases_activity(graph, u, v, key):<EOL><INDENT>print(line, '<STR_LIT>', bel)<EOL>find_related(graph, v, data)<EOL><DEDENT>elif has_degradation_increases_activity(data):<EOL><INDENT>print(line, '<STR_LIT>', bel)<EOL>find_related(graph, v, data)<EOL><DEDENT>elif has_translocation_increases_activity(data):<EOL><INDENT>print(line, '<STR_LIT>', bel)<EOL>find_related(graph, v, data)<EOL><DEDENT>elif complex_increases_activity(graph, u, v, key):<EOL><INDENT>print(line, '<STR_LIT>', bel)<EOL>find_related(graph, v, data)<EOL><DEDENT>elif has_same_subject_object(graph, u, v, key):<EOL><INDENT>print(line, '<STR_LIT>', bel)<EOL><DEDENT>else:<EOL><INDENT>print(line, '<STR_LIT>', bel)<EOL><DEDENT><DEDENT>
Find edges that are A - A, meaning that some conditions in the edge best describe the interaction.