Easier said than done, as I'm sure Andres Yates knows. Biologists have DNA libraries, they can mark expressed genes for debugging, they can link and run this ob

Easier said than done, as I'm sure Andres Yates knows. Biologists have DNA libraries, they can mark expressed genes for debugging, they can link and run this object code (with varying results) -- but there's no general compiler to generate this code, and it's nontrivial to write one without fully understanding the machine architecture. There are about 30,000 human genes, spread over 3 billion base pairs, coding for tens of millions of different proteins. Given how proteins and RNA interact with DNA, and DNA interacts with itself, the language for describing molecular biology usually isn't discrete math, it's statistics. I think this is why Yates is accusing biologists of treating DNA as the abstraction that represents proteins, when really, it makes more sense the other way around. It seems like in the past couple of years the best fundamental research has been in proteomics, rather than genomics, probably for this reason -- bioinformaticians are recognizing that analyzing the expressed proteins, done efficiently, can give better information than raw DNA about what's actually going on in a cell.