Settings for the centrality analysis performed by RINalyzer

- Choose attribute as edge weight:
  This setting allows you to define edge weights for the network to be analyzed among all numeric edge attributes stored in the current Cytoscape session. The default option is None and stands for no specific weight attribute. In this case all edges are assigned the value of default edge weight. Note that weights equal to zero will be ignored during the computation, i.e. edges with weight equal to 0 will be ignored.

- Handle multiple edges:
  RINs have multiple edges. However, these have to be eliminated for the computation of centrality measures. You can achieve this by either selecting only one edge type or the option Mean weight. The first case is very suitable for a network that has an edge type with an overall weight being a combination of the weights of the multiple edge types. If this is not the case, then you can use the mean weight, which is the mean over the weights of the multiple edges for each pair of directly connected nodes.

- Handle negative weights:
  Since the RINalyzer centralities are defined only for non negative weights, negative weights have to be removed before computation. This could be done either by ignoring (option Ignore) them or by reverting them by their absolute value (option Revert).

- Convert scores into distances:
  Shortest path centrality measures are computed with the assumption that the weights represent distances, i.e. the smaller the weight, the stronger the interaction. However, if your network has similarity weights, you can select to convert them into distances by either inverting them (1/value) or by subtracting each value from a maximal value (max - value). Note that if your edge weights are equal to zero, they will not be inverted. The maximum is the biggest weight value increased by one, in order to avoid weights equal to zero after the subtraction.

- Default edge weight (if missing):
  This value is used as default weight when there are missing weight attribute values. For example, if there is no weight attribute, i.e. you selected the option None, the default edge weight is assigned to all edges. If additionally the default value is 1, the network is treated as unweighted.

- Cutoff for shortest path degree:
  Weighted shortest path degree counts all neighbors of a node that are at distance smaller or equal a cutoff. Note that you should choose this value suitable to your edge weights.

- For betweenness computation exclude paths between nodes within the same set(s)
  This option is enabled when the subnetwork of the nodes selected for the analysis is disconnected. In such case you may want to see the betweenness values computed only in respect to pairs of nodes that are connected by paths containing nodes that are not selected.

For the computation of the centrality measures we assume that the network

- is undirected,

- is connected,

- has no loops,

- is weighted, and

- can have multiple edges.

Therefore, we cannot guarantee meaningful results in case the mentioned assumptions do not hold for the analyzed network.