Digital Genes

In living things, genes generate the structures of life using a set of basic building blocks that can be combined and tweaked in multiple ways to create the structures required to allow the creatures survive in the environment.

In GA algorithms, the digital gene sequence needs to be translated into a function that performs successfully in the problem space. The question is, what are the basic building blocks that should be used and how should they be combined and tweaked ?

In living things, the protein is the smallest unit that is combined and tweaked. What is the GA version of this ?

My current thought is that these basic units could be discovered using GAs. By setting the problem environment to a random state, various combinations micro units could be used to create functions, and scored based on the amount of change they cause to the environment state ,either positive or negative, thereby creating a set of building blocks that are not inert (are reactive) when used to try and solve a problem.

The micro units would be functions like boolean conditions, boolean functions, arithmetic operations, storage of values and retrieval.

If this proves unsuccessful, I may try using functions as the GA alternative to proteins.