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Mathematical Biology Is Our Secret Weapon In the Fight Against Disease (scientificamerican.com)
An anonymous reader shares excerpts from a Scientific American article: In recent years, increasingly detailed experimental procedures have lead to a huge influx in the biological data available to scientists. This data is being used to generate hypotheses about the complexity of previously abstruse biological systems. In order to test these hypotheses, they must be written down in the form of a model which can be interrogated to determine whether it correctly mimics the biological observations. Mathematics is the natural language in which to do this. In addition, the advent of, and subsequent increase in, computational ability over the last 60 years has enabled us to suggest and then interrogate complex mathematical models of biological systems. The realisation that biological systems can be treated mathematically, coupled with the computational ability to build and investigate detailed biological models, has led to the dramatic increase in the popularity of mathematical biology. Maths has become a vital weapon in the scientific armoury we have to tackle some of the most pressing questions in medical, biological and ecological science in the 21st century. By describing biological systems mathematically and then using the resulting models, we can gain insights that are impossible to access though experiments and verbal reasoning alone. Mathematical biology is incredibly important if we want to change biology from a descriptive into a predictive science -- giving us power, for example, to avert pandemics or to alter the effects of debilitating diseases.
Mathematics is really great, surely it must have some application in biology, but the article is more about potential that actuality.
Are they suggesting that the characteristics of physical systems can be represented by mathematical equations? And that these mathematical models may be used to predict the characteristics of physical systems that may not even exist yet?
My God, who would have ever thought this possible or valuable? They are leading biological science boldly into the 17th century!
If only there was some device and a standardized language with which to create these mathematical models without having to completely defined the models in closed form. Perhaps to "simulate" (to coin a phrase) these systems in an abstract way.
Obligatory xkcd.
Devil's advocate here:
Pandemics have saved the world before. Before the Black Plague, the life of most people in the Western world was of groaning slavery as a serf with infant mortality off the charts and an average lifespan less than our current drinking age here in the US. The Black Plague, once the ruling class had too few backs to flog, eventually made life bearable, if not prosperous for the average person. Instead of subsistence farming, luxury items like olives could be grown. Trade increased, and the Renaissance happened. Had the plague not happened, Europe would still be under tiny little dukedoms and duchies still fighting it out today.
Look at modern times. We are heading back to that scenario. Revolutions are pretty much pointless where one helicopter can turf thousands of protesters or empty a town of life with a Sarin gas canister. It is only a matter of time before we go back to groaning serfdom worldwide again. It might just be another pandemic might save the world as we know it, allowing technology and advances to prosper again.
You just revealed our secret weapon to the germs!!!! Now they will find a defense against our mathematics!!!
General Relativity: Space-time tells matter where to go; Matter tells space-time what shape to be.
Douglas Adams is chuckling to himself. The answer to life the universe and everything really is 42.
Digital is, by definition, imperfect. Analog is the way to go.
TFS was a fantastic sales pitch.
Now show me how mathematical biology can showcase its benefit.
I might note that over the last 60 years, we've seen everything from AIDS to Zika attack mankind, so pardon me if I'm skeptical as hell as to it's ability to predict or avert pandemics. Sadly, even Ebola enjoyed a fashionable resurgence after a 20-year hiatus.
It's also rather obvious that great financial benefit stems from perpetually treating issues rather than curing them, proving that the ultimate virus that has yet to be eradicated is Greed.
I'm a physicist working on tools that quantitatively measure biologic interactions. A common use for my tools is for a pharma company to take a set of molecules that they have determined through modeling will interact (inhibit activity, enhance activity, etc.) with a target protein and we measure whether that actually happens directly at the molecular level.
So why hasn't this been done before?
Biology is not just complex, it's also very often overgeneralized and poorly understood. It's dogma (literally) in biology that a cell using a particular sequence of DNA to build a protein will always build the same protein. This is not true. Two "identical" proteins are almost certainly chemically different. Biology to date has dealt with collections and statistical averages of protein function and genetic activity. The measurements used to work in biology, to date, use simplified environments (gels, buffers, simplified model organisms) and reporting methods that interfere with the molecular function of the biological system (fluorescence, dye binding), but these methods and approaches have been necessary to make progress.
At this point, most biologists either have forgotten, or never appreciated, that these systems are measuring secondary effects and generalizations of true biological function. Convincing them that a quantitative, direct, math-and-physics based approach to biology can produce helpful information is an enormous cultural challenge. When presented with data showing that a correlative measurement (i.e. fluorescence) disagrees with a direct physics based measurement (i.e. an electronic biosensor), biologists will tend to believe the secondary measurement over the direct measurement.
As direct measurement tools and simulations become more widely used, there will need to be a change in the way biologists think about their measurements, and that's not going to be a comfortable thing for them. There is an opportunity for folks in computational and physical science to lead the way and show them that our approaches to problem solving are valid and helpful.
I think natural language is better than math for modeling nature. Math relies on axioms of consistency and transitivity that nature is not constrained by. Math is unnatural to interrogate, whereas natural language is, well, natural to us and therefore it is easier to interrogate a model using natural language.
Natural language is the natural language to model nature. Math is too constrained by philosophical assumptions about consistency.
That word is rather ... abstruse.
https://www.xkcd.com/793/
P.S. I was a physics major, once upon a time.
P.P.S I am guilty of having done what is portrayed in that comic.
P.P.P.S I had a physic prof comment on me looking down on chemistry, "as you should." I *think* the comment was tongue-in-cheek.
Human biochemistry reveals wrinkles we did not know about all the time. A company might spend a billion dollars developing a drug only to find in clinical trials that some previously unknown enzyme or receptor or feedback mechanism makes the drug unmarketable. Mathematical models can't work well if there are these unknown sitting there waiting. They can't be predicted. They have to be found the hard way by wet biochemistry investigation. It would be like trying to use math when new integers keep showing up between the old ones.
If Slashdot were chemistry it would look like this:Cadaverine
Science is predictive. Period. Get on our level biology.
While lkoklp