The density of the predictions generated by the top rule of the Blosum62 GP

R code of the min-max function GP can be requested from the

a an email.

y

pter has introduced how the genetic programming approach can

o provide another way to discover intelligent rules for the peptide

iscovery. The most striking features of the genetic programming

are its great interpretation capability as well as the possibility of

ng the optimal rules without exhausting all possible candidates.

pter has introduced the min-max function, which is especially

r dealing with the protease cleavage pattern discovery. In addition,

se Polish notation has been used to express the chromosomes of

mimicking an evolution process for the optimal solutions. How

tion operator, the dual-chromosome operator and the single-

ome crossover are designed and used for breeding new RPN

omes of rules has been introduced and demonstrated in this

as well. In order to avoid the possibility of a homogeneous

n and increase the diversity among candidates in a GP pool, the

alled the revolution has been introduced. This chapter has applied

ic programming approach with the min-max function to the factor

ase cleavage data analysis. The resulting decision-making rule

good discrimination power and has a good interpretation

y.