As large quantities of genomic sequence data began to accumulate in public databases, genetic algorithms became important to decipher the enormous collection of genomic data. They are commonly used to generate high-quality solutions to optimization and search problems by relying on bio-inspired operators such as mutation, crossover and selection. The followings are commonly used genetic algorithms:
* AntiSMASH (Antibiotics and Secondary Metabolite Analysis Shell) addresses secondary metabolite genome pipelines.
* PRISM (Prediction Informatics for Secondary Metabolites) is a combinatorial approach to chemical structure prediction for genetically encoded nonribosomal peptides and type I and II polyketides.
* SIM (Statistically based sequence similarity) method, such as FASTA or PSI-BLAST, infer orthologous homology.
*BLAST (Basic local alignment search tool) is an approach for rapid sequence comparison.