At the BSDB meeting, Michael White (University of Manchester), pioneer of the imaging of gene expression in living cells, gave one of his customarily sound, interesting, inspiring and enlightening talks in which he discussed his work on the dynamics of NFkB expression and its regulatory consequences. The accumulation of measured variables and the dynamic nature of the information gathered by his experiments demand models and, in the course of the talk, he managed to slip some statements about why do we need models in Biology. And I do not think he meant Cell/Nature or Science Figure 9 models (a collection of gene names joined by arrows which satisfy editors but fail to capture the reality they aim for) but rather actual dynamical systems which incorporate the variables, test the hypotheses under consideration and generate new hypotheses. Most important, the models he was talking about are quantitative and make us think quantitatively. Curiously Genetics and Biochemistry have very strong foundations of this kind but the gene hunt that has characterized Biology over the last few years have made us forget this and over the last few years some of us have been discovering that Natural Selection has not just been shaping the DNA landscape but also the output of the information contained there in the form of numbers.
The gathering of quantitative data which incorporate a dynamics have, since the time of Newton, required models that uncover the relationships between the variables, reproduce (or not as it may be the case) the situation being modelled and either make predictions or generate more experiments. Mike made these points beautifully and insisted on what some of us believe, namely that as Biology becomes data rich, models become an integral part of our work. However, for the most part, biologists, cell and molecular biologists in particular, do not know how to develop models, and much less how to use them. Enter the theorist.
Models require an uncanny ability to read data, abstract, find relationships between variables and make testable predictions. In some instances, models can give rise to Theories. The theorist is a figure common in the physical sciences, particularly Physics, whose job is to generate models from data and to provide theories that explain the phenomena. Theoretical physicists do not do experiments but they get others to do them. Sometimes at a huge public expense; the search for the Higgs Boson is a very good example of this. There is an asymmetry here because while theorists do not do experiments, experimentalists do modelling and sometimes also theory; although they engage in discussions with theorists, in Physics and, more so in Chemistry, experimentalists really do not need them and they will enjoy dealing with their own data. Biology is different. Excluding certain areas of population biology and, certainly, epidemiology, there are no theorists (a la Physics) in Biology. However, as quantitative data in cell, molecular and developmental biology has began to emerge, it is acting as a baie for physicists. The reasons are complex. Perhaps it is because, outside certain aspects of Astronomy, there is not much of high caliber left in need of an explanation in Physics; String Theory, as a physicist explained to me a while ago is an example of the problem because it is neither Physics –because one cannot do experiments on it – nor mathematics –because one cannot prove completely much of it. Chemistry is a different matter but here, Schrodinger’s equation and what follows said the fundamental and whereas much of what is alloy cannot be totally understood (in the predictive way physicists like), a lot of what is around are ‘details’, important but details and, in any case theory and experiments go together. Biology is an open book of blank pages with lots of facts and limited understanding. Perhaps this is what makes it attractive to theorists. Be that as it may, over the last few years there has been a steady influx of physicists into Cell and Molecular Biology which is now peaking. For the most part, this is being very positive and the physicists are making good contributions. An interesting aspect of this influx is that they get very close to the data, to the experiments. For the moment in Biology, there is no room for Einsteins, Boltzmanns, Schroedingers or Heisenbergs, not sure how much room there is for theory but sure there is room for people who can help us deal with the data, model it, extract principles and understanding. Above all, demand numbers from us and teach us their value. The role of the physicists is to help us sort the messy data produced by our experiments and, in some instances of Cell Biology, help us design experiments. This is very fine and very fun, and those of us who have had the pleasure of collaborating with physicists in our work, know how valuable and inspiring these interactions are.
Physicists who turn to Biology come in different flavours but the best ones, in my view, are the ones who to a larger or lesser degree become experimentalists. Some names come to mind, but this is not the place for namedropping. There are others who are purely theoretical and this, again, come in two flavours. Ones align themselves to a particular group and work very closely with it to improve the experiments, generate data and provide insights.; they engage with experiments. There are others who move from place to place looking for data they can model. The latter are, these days, taking advantage of the fashion and the interest and need that biologists have of them. It is with this latter class that I have an issue.
Many years ago, the early 80s, A. Garcia Bellido (of clonal analysis in development fame) had a bee in his bonnet on theorists and Biology. He told me that he did not respect theorists in Biology because theorists could produce a theory and be wrong and nobody would care, they then would go on to produce another theory tomorrow without a blush. On the other hand if an experimentalist makes a mistake, that could be it; the blotch will remain. Those were other times, but he still might have a point today. The problem in my view does not lie with the theorists but with us. We should get ownership of our data, we should learn how to model, we should learn how to theorize. A physicist whom I know well and respect a great deal claims to be disarmed without data, that without data her work is disabled. Every time I hear this I scream inside: and what about us? Experimentalists are as disabled without data as a theorist. The difference between the experimentalist and the theorist is that we (the first ones) cannot choose the data we work with, theorists can……..as long as we allow them to.
My friend Jeremy Gunwardena has argued that Biology is more theoretical than Physics and he may have a point, but within reason and one day I should (and will) take him to task on this matter. But in the meantime the point I want to make here is not that different from his. Biology has much that is theoretical, after all every experiment tests (or should test) some hypothesis and in that sense, formally, it is a theory. What has changed over the year, what is making the difference, is that the data now is quantitative and this will require a new kind of model. Population biologists and epidemiologists are versed in modelling, but what they do is unlikely to be for cell and molecular biologists; we have to learn to do that so that if we share our data with a theorist, we know what we are doing.
As I have said above, models can, on occasion, lead to Theories and there is very little of this in Biology though the work of G. Mendel, C. Darwin, R. Fisher and H. Driesch could fit these categories though, remarkably, all of them did a great deal of experimental work. At the moment there is a fertile ground that stems from the interactions of physicists and biologists but I can see a future in which biologists catch up and we have a new science, we could call it the Physics of Living Matter. In the end, Biology is a chapter of Physics.
NB1. For a very lucid account of the role of the theorist in Biology, read F. Crick “what a mad pursuit’. Although the questions are not huge these days, the guidelines for the work are, in my view, very well laid out here.
NB2. Two important readings on this matters:
Cohen JE (2004) Mathematics Is Biology’s Next Microscope, Only Better; Biology Is Mathematics’ Next Physics, Only Better. PLoS Biol 2(12): e439. doi:10.1371/journal.pbio.0020439
Roth, S. (2011) Mathematics and Biology: a kantian view on the history of pattern formation theory. Dev Genes and Evol. 211, 255-279.