The effective mutation rate that supplies high success rate and small computational costs is examined for different weightings of the fitness function.
They can pick up cellular genes, which are modified by high viral mutation rates, before being supplied as oncogenes to a new host cell.
For the three initial population sizes we consider here, N0 = 10, 104 and 10, an effective population size given by N e ≈ DN0 [ 1], and mutation rate μ = 10-6, the mutation supply rates are S s = 0.001, S m = 0.1 and S l = 10 for the small, medium and large populations respectively.
The limiting speed is proportional to μ1/2 and μ1/3 in linear and planar habitats, respectively, where the mutational supply μ is the product of mutation rate and local population density.
Significantly mutated genes (SMGs) were defined as the somatic mutations with higher mutated frequency than background mutation rate.
We therefore examined how changing mutation rate and population size, while keeping mutation supply rate fixed, influenced the results of our simulations.
Owing to the help from the outside, the tumor gets blood supply, grows, has an increased mutation rate (Gupta and Massague 2006; Sahai 2007).
The mutation supply rate is the product of mutation rate and effective population size, S = N e μ.
The mutation supply rate is the product of population size and mutation rate.
To keep the mutation supply rate constant, it was necessary to increase the mutation rate for the small populations.
Because the evolution of resistance depends greatly on the mutation supply rate (i.e., the combined effect of population size and mutation rate), mechanisms that increase the mutation rate are likely to increase the rate of resistance evolution as well.
