Hi folks, I'm a new graduate student in biology. I'm interested in doing theory (either simulations of biomolecules, physical models of the brain/consciousness, or models of cellular dynamics). I have had very intriguing discussions with fellow students along the following lines: 1. There are two approaches to theoretical/computational biology. One is computational statistics, and the other is called, by the statisticians (computer scientists) "rule based modelling", i.e. normal theoretical science. 2. There is no point to theoretical science in biology. Why use molecular dynamics to figure out exactly how a protein moves when you can just do linear regressions on carefully performed experiments to determine which drugs bind or not? Needless to say I find these views disagreeable (to be clear, some students from a stats background are more extreme than others, and some of the extremeness may be been caused by the imbibing of alcoholic beverages) but I think taking the strong view, that mechanistic, ground up approaches to biological problems are inferior to computational statistics creates for a more interesting discussion. I was curious to know what people make of these views, and, in particular the following: 1. What evidence is there that mechanistic modeling in biology and other fields has been successful? I like to trot out Maxwell and transistors as examples of this but I don't know how robust they are. 2. Which areas of mechanistic modeling in biology do you think could produce impressive results in the future?