def neurommsig_topology(graph: BELGraph, nodes: List[BaseEntity]) -> float:
nodes = list(nodes)<EOL>number_nodes = len(nodes)<EOL>if number_nodes <= <NUM_LIT:1>:<EOL><INDENT>return <NUM_LIT:0.0><EOL><DEDENT>unnormalized_sum = sum(<EOL>u in graph[v]<EOL>for u, v in itt.product(nodes, repeat=<NUM_LIT:2>)<EOL>if v in graph and u != v<EOL>)<EOL>return unnormalized_sum / (number_nodes * (number_nodes - <NUM_LIT:1.0>))<EOL>
Calculate the node neighbor score for a given list of nodes.

    -  Doesn't consider self loops

    .. math::

         \frac{\sum_i^n N_G[i]}{n*(n-1)}