Genetic Algorithm Search
Consider a set S
= ( g1
, , g2
) of k
: the statistic of gene i
: the mean of statistic of all background genes.
A GA is a heuristic search algorithm inspired by natural process of evolution, “survival of the fittest”. The evolution begins with a population, a set of random chromosomes. In each generation, the fitness of every chromosome in the population is evaluated
though a fitness function, and then some are selected to undergo further modification: ‘crossover’ and ‘mutation’. The elitism allows certain number of fittest individuals to be survived for the next generation. This process is repeated until certain termination
conditions are satisfied. The typical GA flow is depicted in Figure 1
. Flowchart of the GA used to find the phenotype-responsive sub-networks.