Figure 4.

Characteristics of the C. jejuni protein network. (a) Degree frequency distribution for the entire two-hybrid dataset (CampyYTH v3.1). k = degree, the number of connections to a protein. P(k) = the probability that a node has k connections. A power law fit yields: y = 0.4153 x^-1.29; R² = 0.88. (b) Degree frequency distribution for the high confidence dataset (confidence scores > 0.5). A power law fit yields: y = 482.2 x^-1.53, R² = 0.89. (c) Rank-degree distribution for the entire two-hybrid dataset. The semi-log plot more closely fits an exponential curve (red line, R² = 0.97) than a power law curve (black line, R² = 0.81). (d) Rank-degree distribution for the high confidence data. The semi-log plot more closely fits a power law curve (black line, R² = 0.91) consistent with a scale-free network. (e, f) The distribution of the average clustering coefficient (C) for degree k for the entire two-hybrid dataset (e) and the high confidence set (f). C is equal to the number of interactions among a protein's interactors as a fraction of all possible interactions. (g) Frequency of pathlength (the shortest distance in interactions between two nodes) for the entire dataset. (h) Frequency of pathlength for the high confidence data.