Table 1.
NAP’s supported topological features and their explanation
| Topological feature | Simplified explanation |
|---|---|
| Number of edges | Shows the number of edges in the network. Moderate network of several thousand connections are very acceptable |
| Number of nodes | Shows the number of nodes in the network. There is no limitation on the number of nodes |
| Diameter | Shows the length of the longest geodesic. The diameter is calculated by using a breadth-first search like method. The graph-theoretic or geodesic distance between two points is defined as the length of the shortest path between them |
| Radius | The eccentricity of a vertex is its shortest path distance from the farthest other node in the graph. The smallest eccentricity in a graph is called its radius. The eccentricity of a vertex is calculated by measuring the shortest distance from (or to) the vertex, to (or from) all vertices in the graph, and taking the maximum |
| Density | The density of a graph is the ratio of the number of edges and the number of possible edges |
| Number of edges | Shows the number of edges in the network. If the has more than 10,000 edges it will take into account the first 10,000 |
| Average path length | The average number of steps needed to go from a node to any other |
| Clustering coefficient | A metric to show if the network has the tendency to form clusters |
| Modularity | This function calculates how modular is a given division of a graph into subgraphs |
| Number of self-loops | How many nodes are connected to themselves |
| Average eccentricity | The eccentricity of a vertex is its shortest path distance from the farthest other node in the graph |
| Average eigenvector centrality | It is a measure of the influence of a node in a network |
| Assortativity degree | The assortativity coefficient is positive is similar vertices (based on some external property) tend to connect to each, and negative otherwise |
| Is directed acyclic graph | It returns True (1) or False (0) |
| Is directed | It returns True (1) or False (0) depending whether the edges are directed or not |
| Is bipartite | It returns True (1) or False (0) depending whether the graph is bipartite or not |
| Is chordal | It returns True (1) or False (0). A graph is chordal (or triangulated) if each of its cycles of four or more nodes has a chord, which is an edge joining two nodes that are not adjacent in the cycle. An equivalent definition is that any chordless cycles have at most three nodes |
| Average number of neighbors | How many neighbors each node of the network has on average |
| Centralization betweenness | It is an indicator of a node’s centrality in a network. It is equal to the number of shortest paths from all vertices to all others that pass through that node. Betweenness centrality quantifies the number of times a node acts as a bridge along the shortest path between two other nodes |
| Centralization closeness | It measures the speed with which randomly walking messages reach a vertex from elsewhere in the graph |
| Centralization degree | It is defined as the number of links incident upon a node |
| Graph mincut | It calculates the minimum st-cut between two vertices in a graph The minimum st-cut between source and target is the minimum total weight of edges needed to remove to eliminate all paths from source to target |
| Motifs-3 | Use of igraph to searches a graph for motifs of size 3 |
| Motifs-4 | Use of igraph to searches a graph for motifs of size 4 |