[alexholehouse]

As someone working in computational biology, the problem is really bigger than just understanding the individual components. There's this huge (and totally understandable) bias in biology to look at the things which are easy to look at using techniques we have developed, and to model things using concepts and models developed for similar things (such as in chemistry and physics).

The problem is this creates a set-up where we're looking at a lot of the same things in a lot of the same ways, which makes things look fairly similar. This doesn't necessarily accurately reflect the reality. It's an obvious starting point, and as the data capture technologies involved become more advanced it's clearly the way to guide future experiments, ideas and development, but it also leads to a situation where a lot of the critical factors in various complex processes aren't being looked at in the right way.

That's not to say, of course, that this is a problem unique to biology - quantum mechanics represents a pretty good model of fundamental particle physics, but its likely it doesn't actually reflect what's going on. That's not to say that the advances brought by QM haven't been huge, and ultimately there comes a point where if a model is indistinguishable from the reality using all our methods then can you really say the two are different? Philosophical discussions for another day, me thinks...