code: def neurommsig_topology(graph: BELGraph, nodes: List[BaseEntity]) -> float:
      
      nodes = list(nodes)
      number_nodes = len(nodes)
  
      if number_nodes <= 1:
          # log.debug('')
          return 0.0
  
      unnormalized_sum = sum(
          u in graph[v]
          for u, v in itt.product(nodes, repeat=2)
          if v in graph and u != v
      )
  
      return unnormalized_sum / (number_nodes * (number_nodes - 1.0))
docs: 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)}