Apply genetic algorithm with an adaptive stopping criterion to PCR-RFLP Primer Design

Abstract

Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) is usually applied to small-scale basic research studies of complex genetic diseases that are associated with single nucleotide polymorphisms (SNPs). Before performing PCR-RFLP for SNP genotyping, the feasible primer pair and the available restriction enzymes for discriminating the target SNP are required. This is a tedious and time-consuming task when using manual search without any computer assisting. Genetic Algorithm (GA) has been widely applied to many fields and yielded good solutions. However, in many used GAs, the number of generations are usually fixed and make them are inefficient in determining their adequate terminations. In this paper, we use GA with an adaptive stopping criterion to implement the PCR-RFLP primer design. The different numbers of generations are used to perform the PCR-RFLP primer design, and the adaptive generations are also observed and discussed.