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Mathematical Biology Is Our Secret Weapon In the Fight Against Disease ( 57

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.
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Mathematical Biology Is Our Secret Weapon In the Fight Against Disease

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  • by XXongo ( 3986865 ) on Friday June 16, 2017 @11:47AM (#54633439) Homepage
    The article doesn't really show much in the way of mathematics used in biology. It's rather more cheerleading for mathematics in biology than really showing its power.

    Mathematics is really great, surely it must have some application in biology, but the article is more about potential that actuality.

    • by Jamu ( 852752 )
      I'm wondering what they were using before...
    • Even the stock photo.

      "Hey, we got an article about math and biology... Hmm... what about this image? [] Or This? [] No, what the fuck am I talking about? That's math! Biology isn't math! Biology is slimy and fuzzy, not math! Definitely go with a decades old picture of Ebola using EM which is nearly 100 years old. Yup, definitely, math is useful to biology in that engineers and physicists build toys like electron microscopes for biologists to get slime all over."

      For the record, I'm firmly in the category of b
  • by Brett Buck ( 811747 ) on Friday June 16, 2017 @11:51AM (#54633465)

    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.

    • by Anonymous Coward

      No, they've known it for ages. Hardy-Weinberg dates to 1908, Lotka-Volterra to 1910. Ideas of exponential and geometric growth have been around much longer.

      Mathematical models for HIV infection were created within years of the discovery of AIDS.

      This article is not news.

    • This is why I take "expert" dietary recommendations with a huge grain of salt ( which isn't, as it turns out, the devil it once was. Joining coffee and eggs on the pile of things which "may or may not be good or horrible for you" ).

      It's staggering not only how much we don't know about how our bodies really work, but also how confident "we" are in what we only think we know. I'm also amazed at slow new information is propagated out. For instance; we knew in the 80s, the 80s that fat wasn't the dietary enemy that had been made out in previous studies ( well, "studies" given their methodology included throwing out data that didn't agree with their conclusions ), yet it would take another 30+ years before that started becoming general knowledge. In the meanwhile, increased sugar based diets ravaged the population.

      We're still just stumbling around blind on this.

    • by Anonymous Coward

      You sound like someone who has no real insight into the problem. I work at the intersection of mechanistic and quantitative sciences.

      The issue is not everything is quantitative, and mathematics is only really good for things you can quantify. There is a reason why math is the handmaiden of physics, less so chemistry, and even less so biology.

      Biology has a tremendous amount of representations that are "mechanistic" and are useful in that form. Forcing that kind of representation into a mathematical mold make

    • You're being flip, but the problem is that even the most simplest biological systems cannot be simulated. Its not that we don't know the math, but the math in intractable. Just calculating a simple physical property, like solubility of a particular protein, will bring the fastest supercomputers to their knees.
  • by Anonymous Coward

    Obligatory xkcd [].

  • by sconeu ( 64226 ) on Friday June 16, 2017 @12:37PM (#54633861) Homepage Journal

    You just revealed our secret weapon to the germs!!!! Now they will find a defense against our mathematics!!!

  • Douglas Adams is chuckling to himself. The answer to life the universe and everything really is 42.

  • 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 ha

  • by Goldsmith ( 561202 ) on Friday June 16, 2017 @01:24PM (#54634333)

    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.

    • Re: (Score:2, Interesting)

      by Anonymous Coward

      I'm an engineer that works with biologists doing academic biological research. I'm going to have to disagree on some points, or at least ask for clarification.

      The example you gave of "dogma" is definitely not held as sacrosanct among biologists. There are a wide number of well understood mechanisms that lead to varying protein structure based on a single DNA sequence. While its often a working assumption the DNA translates to protein through a direct and repeatable route, which is many ways is a good assump

      • I wish this person had logged in to respond to my comment.

        There is a difference between academic collaboration, that carries with it added resources and funding, and making a decision to change the tooling in your lab. When AFMs are standard in biology labs, then it's an acceptable biology tool. Right now, they're an acceptable tool for an engineer or physicist to use when helping a biologist. That's very good, but we're not all the way there.

        Another way to look at this is that there are no collaborators f

    • []

      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.

      • And the obligatory followup: []
      • That's a good one!

        It's our responsibility as physicists to maintain our reputations. That's generally done by covering our ears, closing our eyes and saying "LA LA LA LA" really loud whenever anyone starts talking about complex and interesting problems in the other sciences. (It's either that, or claim to have "already solved that problem 50 years ago.") I forgot to do that once, and now I work with biologists every day.

  • 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
    • Reminds me of this quote, “Logic excludes – by definition – nuances, and Truth resides exclusively in the nuances.” - Ernest Renan

It has just been discovered that research causes cancer in rats.