k i ¼
X
j
A ij
ð3Þ
The degree distribution helps classifying networks according to
models (random, regular, small-world). Notice that protein contact
networks escape classification, roughly described as small-world
networks, albeit presenting key features of random networks
(such as, Gaussian degree distribution).
2. Shortest path: the shortest path sp ij between the i-th and j-th
node describes the lowest number of links connecting the two
residues (see Fig. 3). Algorithms to solve the shortest path
Fig. 2 The recoverin’s three-dimensional structure (left) is translated into a network, graphically represented
by means of the matrix plot of the adjacency matrix (right). Reprinted with permission from [11]
Fig. 3 Graphical representation of a graph with eight nodes and 13 total links: nodes u and v are connected by
two links (shortest path). Reprinted with permission from [14]
12
Luisa Di Paola et al.
X
j
A ij
ð3Þ
The degree distribution helps classifying networks according to
models (random, regular, small-world). Notice that protein contact
networks escape classification, roughly described as small-world
networks, albeit presenting key features of random networks
(such as, Gaussian degree distribution).
2. Shortest path: the shortest path sp ij between the i-th and j-th
node describes the lowest number of links connecting the two
residues (see Fig. 3). Algorithms to solve the shortest path
Fig. 2 The recoverin’s three-dimensional structure (left) is translated into a network, graphically represented
by means of the matrix plot of the adjacency matrix (right). Reprinted with permission from [11]
Fig. 3 Graphical representation of a graph with eight nodes and 13 total links: nodes u and v are connected by
two links (shortest path). Reprinted with permission from [14]
12
Luisa Di Paola et al.