By that I mean that in biology things are quite... Undeterministic. Working with computer is (except some very rare cases) a work when non-deterministic behavio

By that I mean that in biology things are quite... Undeterministic. Working with computer is (except some very rare cases) a work when non-deterministic behaviour is most likely a bug. It's more or less the same in other hard sciences. In biology (and other non-hard sciences) the systems quite often behave in non-deterministic way. To be clear I don't claim that this non-deterministic behaviour is inherent to biological systems (although it is when we take the quantum limit), but rather that they are so complex that untangling this complexity to get nice casuality is virtually impossible. Add the complexity and lack of understanding _on top of that_. > It also seems illogical to say "nobody understands biology, therefore you cannot hope to". I didn't mean to imply that "nobody understands biology, therefore you cannot hope to". I rather meant to express that (at the current level of our species and tools we have) "biology cannot be understood the same way computers are". IMO of course. Therefore applying the same methodology that you apply to hard sciences (math, phys, cs [, chem?]) may not yield as good results and often doesn't. > If nobody understands much, that makes it more likely an outsider can contribute. I can agree that it's easier for outsider to contribute something to biology than physics, mathematics or CS. However, to contribute meaningfully good grasp of concepts and techniques is necessary. Contrarily to math, theoretical or CS in biology it has to be acquired at the front lines of the battles i.e. in the lab. I agree that bioinformatics has made huge leaps in the recent years, but AFAIK nearly all significant new contributions in biology come from the laboratory work not theoretical considerations.