ring optimization of edit metric codes in dna
Error correcting codes over the DNA alphabet are used as embeddable biomarkers. Error correction provides resilience of identification in spite of sequencing errors. Ring optimization is a type of spatially structured evolutionary algorithm derived from models of ring species in nature. This paper compares the performance of a ring optimizer with a standard evolutionary algorithm at searching for large edit metric codes of a given length and able to correct a specified number of errors. The algorithm also incorporates a novel variation operator called Conway crossover that uses Conway's lexicode algorithm as the basis for a binary variation operator. The ring optimizer is found to yield substantially inferior performance. A new type of statistic, last time of innovation is defined and used to compare the two algorithms. Several improvements to the table of best known edit metric codes are presented. Both algorithms yielded improvements to the table, but the improvements due to the ring optimizer were never better than those located by the standard algorithm and worse half of the time.
dna error correction evolutionary algorithms operators bioinformatics