[jostmey]

Well said.

The study of biology is further complicated by the large number of confounding factors that muddle experimental results. Because of this, it is hard to know exactly when it is appropriate to bring in mathematics. Without a proper understanding of all the variables, math can only get you so far.

[joe_the_user]

Well,

Another way to consider this is that biologists have not pushed back hard enough to mathematicians in the sense of asking for some tools which would allow for just slurping up a vast amount of unstructured, unprocessed data and getting something out of it.

It is certainly true that mathematical modeling as it is done now currently will indeed only get you so far.

But spirit of math in conjunction with physics has been to create tools that allow leaps and bounds. If we want to follow that spirit, it seems appropriate to ask for tools to help with messy things that now can't easily be dealt with. It may not be possible but it seems worthwhile to go all the way to the brick wall and pound on it.

[danieltillett]

Unfortunately biologist have been taken for a ride many times by people selling mathematical snake-oil. For example, the whole field of DNA microarrays [1] turned out to be an illusion woven out of applying complex statistical tools to "vast amount of unstructured, unprocessed data". There really is no way you can gain real understanding from poorly designed and unrepeatable experiments by apply obscure mathematical tools.

1. http://en.wikipedia.org/wiki/DNA_microarray

[j2kun]

Luckily, complex numbers and polynomials are not snake oil.