On the one hand, I agre that the Life Sciences need physics for its precision and potential explanatory power. Its approaches encourages us to search for underlying generalities, and to express these in a quantitative manner. On the other hand, I like to think that biological systems have emergent properties from the cellular to the ecosystem level that are best understood (and communicated) by the tools of these disciplines.

This depends on whether or not we go totally quantitative (curse) or still draw upon it for verification of theory (blessing)

It is helpful to understand the framework of empirical research as this gives some rigor to the arguments developed, but the nature of the human experience is something else which cannot be easily boxed. The ability to reproduce the save set of events consistently is almost impossible in human populations given the variability in human populations. What may produce what is considered correct results at period A, may even with the same population have different results at period B.

Mathematical modelling is a tool. Physics uses the tool of mathematical modelling more that biology (at least historically).

I think it is probably a good idea for biologists to start doing biology using the same methods the physicians use to comprehend complex systems, i.e. theory driven experimentation.

We have centuries of description behind us, now it's time to start deriving some general principles of life...

I appreciate Issam's comments and I try and deal with this issue (albet briefly) in my Practice of Quantitative Methods paper ; classical physics deals with closed systems while human systems (including human researchers who study physics) operate in open systems where you would not expect regularity and good predictions - the systen itself is capable of change. Indeed this the essence of the Lucas critique . This is a quote from me "change may be so systemic that the underlying relations themselves are altered, and past empirical regularities captured by the modelling no longer hold in a period of regime change (Lucas, 1976)." The paper from which the quote comes from is

Kelvyn Jones (2010) An Introduction to Statistical Modelling, 241-255. In Theory and Methods in Social Research.

which is downloadable from my Mendely site

http://www.mendeley.com/profiles/kelvyn-jones/

In this answer the word "physics" refers exclusively to Classical Physics. Ecologists, biologists, economists and social scientists  are wrong to envy physics and its methods. The primary objective of physics is to study how the "physical" Universe is made and how it works. I believe this concept can be also extended to biology. The primary objective of biology is to study the Universe "of life," how it is made and how it works. Physical phenomena are reversible however while biological phenomena are not. All physical phenomena can be broken up into many small subsystems so as to be easily studied. It is possible to construct simple mathematical models dependent on a few parameters related to the simple functions of a few variables that quantitatively and throroughly describe the system and how it works. Once properly assembled, all these simple mathematical models form a mathematical model of the entire phenomenon, fully functional in all its aspects. The advantages of physical systems are: as complex and complicated as a physical system can be, it is always possible to know all the parameters on which it depends; and it is always possible to study each parameter individually. Therefore physicists have chosen to study simple phenomena with simple mathematical models. And as a consequence they always make a good impression. At the beginning I circumscribed the problem by limiting myself to referring exclusively to Classical Physics. A simple biological system such as a unicellular organism, Caulerpa taxifolia for example, is by far much more complex and complicated than the most complex and complicated physical system we can imagine. Physicists always begin by saying "... we’ll solve the problem without considering attrition, then at the end when we have understood everything, we’ll add attrition ...". Biologists are not allowed to do this, they cannot begin a study on a cell pretending that there is no cytoplasm, no mitochondria or no nucleus. The biological universe cannot be studied in small pieces as can the physical universe. A mathematical model of the physical universe, based on all the parameters of the system interconnected by generally simple mathematical functions, is a dynamic picture of that universe which allows us to measure and quantify everything. A mathematical model of the biological universe is just an identikit into which we must inject dynamism moment by moment with observations, intuitions, adjustments, etc. In addition, a mathematical model of the biological universe is based on only a small number of the parameters that characterize the system. Equations alone are insufficient to explain the workings of the life of fish in the sea because the number of parameters to be taken into account is not only enormous, but perhaps also unknown. The growth function of von Bertalanffy is based on two variables and three parameters. Is it possible that such a simple mathematical model can explain the phenomenon of growth? Of course not. But to measure, quantify and compare the essential features of two living creatures this model is very helpful. Paraphrasing another of Frédéric’s questions ... it's late and I will certainly not lose any sleep over the envy of economists and social scientists.