Figure 2

Schematic of the computational model. Each clone is characterized by its fitness value, and has a neighborhood of 1-step mutants of size L. When a mutation occurs, a random mutant from this neighborhood is selected. For instance in the figure, the initial clone with fitness f₀ gives rise to the mutant . This mutant has access to another set of L mutants, etc. The fitness of each mutant is f₀ + s _i , where the s _i are drawn from an exponential distribution. This can lead to mutants reaching fitness peaks. If for instance all have lower fitness than the mutant , this mutant is considered to have reached a local peak. In the figure, three out of five fitness values of the 1-step neighborhood change as the clone mutates from f₀ to (dark gray blocks). This corresponds to a value of r = 0.6 for the parameter which defines the amount of ruggedness of the fitness landscape (see text).