Trying to use current computer science to work with biology is like using a hammer to reliably modify the behavior of an ant colony. It may work but only in some special cases.<p>Even with the Von Neumann model, we already have ecosystems where many things are interdependent. And the difference is that the actors in the ecosystem are all designed by people who coordinate and communicate in other channels. They have common standards etc. Now imagine having some monolithic open source code with all the libraries mixed into it that has been forked many times and trying to have a process that will change some of the source code to achieve a desired effect, reliably in even THREE random forks. How would you know the side effects of all your changes? All you can do is make some very simple change and gather statistics on how often your change leads to more instability and crashes.<p>You can&#x27;t just edit an organic system with tons of interdependencies. As humans building software we specifically limit the scope of the dependencies, we make protocols and conventions etc. So we can reason about the impact of a change and make the source code we produce more maintainable. How would this apply with DNA?