Techniques from evolutionary computation to implement as experimental approaches in synthetic biology: tests in silico.

Evolution of biological macromolecules in a tube (in vitro evolution) of modern synthetic biology can be reasonably interpreted as the implementation of genetic algorithms (GA) in a biochemical experiment. This area of modern biology and bioengineering needs both new experimental approaches and new mathematical tools. In our report, we simulate how evolution occurs in vitro using the example of selection of RNA control devices (or RNA-based sensors). We demonstrate that heuristic recombination algorithms are significantly more efficient in a test tube evolution model than the standard mutation and crossover operators. We believe that the implementation of new biochemical methods, based on such heuristic algorithms, can significantly improve the efficiency of in vitro evolution.