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Turing Equation Explains how Leopard Spots Develop

BilZ0r writes "A slight modification of an equation developed by Alan Turing in 1952 has been used to show how the patterns of big cats change from kitten to adult markings. Sy-Sang Liaw of National Chung-Hsing University in Taichung, Taiwan, and colleagues set out to replicate these patterns using Turing's equations. But they found they had to do more than just tweak the parameters of the reaction-diffusion equation. Instead they had to assume two stages of spot growth with different rules: the first to get the baby cats their spots, and the second to create the final configurations. It took them a year to find a final solution."

33 of 109 comments (clear)

  1. Not OS X 10.5? by nlogax · · Score: 5, Funny

    Damn, i thought "Spots" was some sweet new feature in OS X Leopard.

  2. Turing test by Anonymous Coward · · Score: 5, Funny

    So how many questions were the leopard spots able to answer?

    Ohwait...

  3. OSX Leopard? by Henriok · · Score: 2, Funny

    And this one day before Apple reveals features of Mac OS X 10.5 Leopard? What are the odds?

    --

    - Henrik

    - when the Shadows descend -
  4. Extracting Sunlight from Cucumbers by Anonymous Coward · · Score: 3, Funny

    Using Turing equations to model the growth of leopard spots reminds me of 2 other types of research. They are (1) analyzing the human navel and (2) extracting sunlight from cucumbers.

    1. Re:Extracting Sunlight from Cucumbers by wambaugh · · Score: 3, Informative

      Considering that reaction-diffusion equations are thought describe (among many, many other things) the propagation of electric waves in the heart, I'd say research understanding the patterns they form is highly worthwhile even if you have no intellectual curiousity whatsoever.

    2. Re:Extracting Sunlight from Cucumbers by Pseudonym · · Score: 4, Insightful

      And if you're an animation TD who has been assigned the task of creating a huge school of fish, each one of which should look different and yet still look like the right kind of fish, you'll be glad that someone has studied the problem of how to model animal markings.

      No, this is not hypothetical. It's real, and it's done today.

      --
      sub f{($f)=@_;print"$f(q{$f});";}f(q{sub f{($f)=@_;print"$f(q{$f});";}f});
  5. Link to article? by pacc · · Score: 2, Informative

    As interesting as the link may be it does not mention any of the new findings in the header.

  6. Great ! by jfclavette · · Score: 3, Funny

    Awesome work guys ! Now on to the applications of this important discovery ! ... Lunch ?

  7. New Adage by DumbSwede · · Score: 4, Funny

    ... no more than a Leopard can change his Turing Equations

  8. This is really getting old by agent+dero · · Score: 3, Interesting

    Sheesh, I'm really sick and tired of this WWDC, Mac OS X speculation... ;)

    But seriously, where in this silly blog posting does it ever talk about the Leopard spots? Is it just me, or is TFA missing here...

    --
    Error 407 - No creative sig found
  9. Tweaking parameters... by posterlogo · · Score: 5, Interesting

    This work is pretty interesting. My concern with complex mathematical models has always been that nearly any phenomena can be perfectly described given enough variables -- pretty much any curve, any pattern, any shape. In biology, when we try to fit models to data, we have to be very careful not to just keep trying to curve fit with more and more complex equations, because in the end we will be left with something that is not biologically very descriptive -- it leaves us with little understanding of the underlying biology. So when I hear these guys had to tweak parameters to make the reaction-diffusion equation fit the data, I am left wondering what biological factors those extra parameters are supposed to define? The original set of equations was meant to model a system with multiple morphogens that diffuse in two dimensions. When they act upon (or are acted upon) appropriate receptors, a particular "phenotype" emerges at that location. I did RTFA, but it doesn't actually say much about these things -- just makes up a dumb analogy with missionaries and cannibals in competition.

    1. Re:Tweaking parameters... by QuantumFTL · · Score: 4, Informative

      These types of nonlinear differential equations are usually very simple in form, and, most importantly, very local, as that is how most biological interaction is mediated. The parameter tweaking should not be considered too alarming when one considers that the number of biological parameters, in the sense of genetic material, involves thousands of degrees of freedom.

      A short (but good) web site about this can be found here. The interpretation of these formulas is fairly trivial, as they describe a diffusion process (common in all biological systems) with a somewhat more complex reactive process, which could be mediated through all kinds of channels.

      This is not akin to fitting a polynomial to the shape of a bone and calling that a "model" - there are obvious interpretations which correspond to very well known processes.

    2. Re:Tweaking parameters... by 0xC0FFEE · · Score: 2, Insightful
      This all look like Fractal Geometry, Cellular Automata, etc where the end result of a computation (a model) presents some resemblance to a naturally occuring phenomena or observation. It's interesting because there is some expressive power to modelize some phenomemon. It is also deceptive in that the model is not built directly from observations from the natural phenomena.

      In machine learning (really statistical modelization), people are interested in developing methods of representing relations. Expressive models can "learn" complex mathematical functions (like the distribution of spots). Because learning uses finite (and sometime noisy) data, it is necessary to limit the expressiveness of the models so that chance occurrences in the data are smoothed out of the representation and only meaninful correlations are retained. Also the model is "objectively" measured. One way to do it is to set aside some of the data and use it to validate the model. That is, try to predict unseen data. If the model performs well on unseen data then it has "learned" a meaningful representation of the function governing the creation of the data. Even then, the model doesn't have explanative power (Correlation doesn't imply causation), just predictive power.

      To link back to the parent: If all you want is description, you rely on the predictive power of the model and there are standard ways to make sure the model is accurate and conservative with respect to the data used to build it. If you want to explain the underlying biological process then: though luck.

      Finally, (I'm officially ranting now) you're asking a lot at the same time. It's like discarding Newton's mechanics because he wasn't aware of all the factors (atoms, quarks, quantum mechanics) even if the model fits reality well. At some point you have to fence the known and unknown and structure what you know into a coherent system of axioms. Then you bite at the unknown a little bit more and try to fit/extend/simplify your system of axioms. I mean, to this day, even if we can predict gravitational phenomena to incredible precision, nobody would be foolish enough to think that they know what gravitation really is; they can predict how it behaves but they can't explain it.

    3. Re:Tweaking parameters... by asuffield · · Score: 2, Insightful
      My concern with complex mathematical models has always been that nearly any phenomena can be perfectly described given enough variables -- pretty much any curve, any pattern, any shape. In biology, when we try to fit models to data, we have to be very careful not to just keep trying to curve fit with more and more complex equations, because in the end we will be left with something that is not biologically very descriptive -- it leaves us with little understanding of the underlying biology.


      The objective of scientific research is to find ways to make useful predictions (almost by definition; if a field of study cannot make predictions or is not useful, it's not science - it's philosophy or art something like that). If you can generate a sufficiently accurate prediction, then the method by which you attain it is immaterial. 'Understanding' the processes is one highly effective way to discover such things, but it's not the only way. These modelling techniques are a good way to bridge gaps in understanding and make accurate predictions. Understanding things is more important for 'pure research' goals - extending the foundations on which you can construct new predictions. There's no reason for concern so long as you keep these things clear and don't confuse them; they have nothing in common except that they're both ways of constructing a prediction.

      However, I am unable to think of a reason why predicting the patterns of leopard spots could be useful, unless you're trying to engage in some form of leopard topiary or need to compress a large number of images of leopards.

      So when I hear these guys had to tweak parameters to make the reaction-diffusion equation fit the data, I am left wondering what biological factors those extra parameters are supposed to define?


      They aren't supposed to define anything. Attempting to do so would be confusing 'modelling' with 'understanding'. For an analogy: you can get mince out of a mincing machine, but no matter how hard you look, you are not going to get any mincing machines out of the mince.

      Those parameters are almost certainly related to some real-world process, but the relationship is very unlikely to be a direct mapping of parameters to factors - and no amount of staring at the equations will result in understanding the unknown expression that defines this relationship. Most likely they are an approximation of the result of the true expression, sufficiently accurate to describe all the real-world cases but otherwise uninformative.
  10. Leopard spots, snail shells, and Leonardo of Pisa by The+Living+Fractal · · Score: 3, Interesting

    I find this kind of research amazing. It's like nature has given us a hint at something, something on the tip a vastly larger and more profound realization. The ability to recognize these natural patterns, such as the Fibonacci sequence, is IMHO one of the fundamental qualities of intelligence and sentience. It seems to be something tied to the very basis of existence, upon which our human minds are a layer with a depth that may indeed have no bounds or may merely be a small slice. The potential infinity of it all is staggering, and yet beautiful, and is the primary reason I chose this handle which I use here.

    Here we witness the micro through the macro, through all scales of physical dimension, in an interplay of force, energy and motion, with the final result happening both all at once and forever spread over time. Incredible.

    TLF

    --
    I do not respond to cowards. Especially anonymous ones.
  11. The point is, you never know. by Elemenope · · Score: 5, Insightful

    Some researchers dicking around with orange molds accidentally discovered this little thing called PENICLLIN. Some Swiss mountain hiker got irritated with little seeds that kept sticking to his clothes, which upon further inspection led to the invention of VELCRO.

    On the other hand, researchers trying to solve a critical rubber shortage during World War II came up with an earth-shattering invention: SILLY PUTTY.

    Point is, you just never know. ;)

    --
    All the techniques ever used to make men moral have been themselves thoroughly immoral... (Nietzsche)
    1. Re:The point is, you never know. by Kj0n · · Score: 2, Informative

      Come on!

      Everyone knows that Velcro was a Vulcan invention.

    2. Re:The point is, you never know. by eclectro · · Score: 2, Funny

      My thoughts exactly. I also bet they scraped penicillin off the aliens found at Roswell too.

      --
      Take the cheese to sickbay, the doctor should see it as soon as possible - B'Elanna Torres, "Learning Curve"
    3. Re:The point is, you never know. by Elemenope · · Score: 4, Informative

      anyhow, i believe you ment bread mold, not orange mold.

      Penicillium is a genus of what are called 'bread molds' which grow, eponymously, on most yeasted breads. However, they also have a strong affinity for orange rind, and oranges make a nearly ideal culture medium for its growth. Penicillin's antibacteriological properties were discovered in a lab when an orange was accidentally exposed to penicillium and then left in contact with a bacteria culture. Hence, for the story about serendipity and science, its affinity for oranges was more pertinent. Oddly enough, this genus provdes us with some of the molds that make some of the tastiest cheese around (esp. Gorgonzola).

      i know the best place to store rubber, place it skin tight on hot girls :D

      I, too, like rubber and girls. ;)

      --
      All the techniques ever used to make men moral have been themselves thoroughly immoral... (Nietzsche)
    4. Re:The point is, you never know. by blackest_k · · Score: 2, Interesting

      silly putty, does have interesting properties.
      it can flow like a liquid and act like a solid when pushed rapidly.
      whats that good for polishing internal holes if you mix an abrasive in with it. Which might help get the best out of high performance engines.

      it's an interesting material wonder how it would cope with a leak in a pressurised container could it contain or slow that leak for a period of time.

      it also bounces and lifts ink off paper.

  12. Re:There is no TAIWAN by Anonymous Coward · · Score: 2, Funny

    [quote]
    The rouge state of Taiwan is part of Peoples Republic of CHINA.
    [/quote]

    Yes, Taiwan is a nice shade of pink, unlike the red commie bastards in China.

  13. Re:Leopard spots, snail shells, and Leonardo of Pi by Planesdragon · · Score: 3, Insightful

    Here we witness the micro through the macro, through all scales of physical dimension, in an interplay of force, energy and motion, with the final result happening both all at once and forever spread over time. Incredible.

    No, not really."

    If you find something as mundane as a mathematical model of how spots deveop on leopards to be "incredible", I think the wonder is all in you and not in the thing itself. Setting aside the wonder that is life itself, leopard spots are pretty boring -- roughly the equivalent to modeling how freckles develop on redheads.

  14. Sounds like by Black+Parrot · · Score: 2, Informative

    cellular automata.

    --
    Sheesh, evil *and* a jerk. -- Jade
    1. Re:Sounds like by VoidEngineer · · Score: 2, Informative

      cellular automata.

      Actually, it's the precursor to cellular autonoma. There's a period of Alan Turrings life, that most people don't study and know about, which involves him studying a number of biological models. His 1952 paper 'On the Chemical Basis of Biological Morphogenesis' contains the foundations of what Wolfram would later go on and call 'cellular autonoma'. Go check it out, and form your own opinion. Having read both Wolfram and Turing, I have to give clear credit to Turing for coming up with the idea of cellular autonoma before Wolfram. That being said, Turing appears to have been interested in it and studying those concepts from a particularly oblique angle than how Wolfram approached them. Wolfram certainly went off and made a study of cellular autonoma unto itself. But Turing came up with the models before Wolfram; Turing just didn't call them 'cellular autonoma' and perhaps didn't view them quite as generically as Wolfram envisioned them.

  15. Re:Leopard spots, snail shells, and Leonardo of Pi by ceoyoyo · · Score: 4, Funny

    I really hope you don't think freckles on, or redheads in general are boring. They're nothing like leopards either.

  16. It's really great !! by himanshuarora · · Score: 2, Interesting

    I remember my professor telling us in the class that anything which can be expressed/solved by any turing machine is an algorithm. Those equations seems different than the description of a turing machine[ To Me :( ]. I would say that it's a great finding. He was able to describe some natural phenomenon from a set of turing equations. It implies that we can simulate the whole world[or a part] on a computer.

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    Spam: Any activity on internet to gain popularity without paying to advertising companies like Google.
  17. This is no big deal by crush · · Score: 3, Informative

    Since at least 1989 (with Dictyostelium) developmental and evolutionary biologists have used Turing's mechanism to explain pattern formation. Good site here

  18. Bible Science by Doc+Ruby · · Score: 2, Funny

    Apparently, old Jeremiah was teaching Turing's mathematics to homeless Israelites when he told one

    "Can the Ethiopian change his skin, or the leopard his spots? then may ye also do good, that are accustomed to do evil."

    If one of the grad students working on this paper is an Ethiopian who's spent the year in a Taiwanese office rather than in the equatorial sun, we might have all the proof we need to test this ancient riddle.

    --

    --
    make install -not war

  19. Turing's Paper by SirClicksalot · · Score: 3, Informative

    For those of you that don't know what this is about:

    This isn't related to Turing's work on early computer science, but concerns research he did shortly before his death.
    Turing proposed that under certain conditions diffusion can destabilize a chemical system and cause spatial patterns.

    His original paper on the subject can be found at the Turing Archive.

    Mathematical biologists have been using these equations to model biological pattern formation for some time. If you want to read up on it, try googling for research by Gierer and Meinhardt on pattern formation

    --
    It is not so much that I have confidence in scientists being right, but that I have so much in nonscientists being wrong
  20. Re:Leopard spots, snail shells, and Leonardo of Pi by Alaria+Phrozen · · Score: 2, Funny

    Well if leopards are anything like lions (they're both big cats, one just seems to have put more points into strength over agility than the other), I'd rather not bother with them. I know one famous lion researcher personally: his first name is Token (but he has been called multiple last names), and he said that "lions are totally gay."

    But now with this research, we can perhaps someday take a baby human child and determine if they will grow up to be the Messiah or Antichrist. We map all their freckles and exactly calculate their resultant pattern. If the final morphology is some sort of hyper-religious symbol (a cross drawn over a Superman symbol with a star and sparklies all over it, a skull-and-cross-bones with burning flames and a dirty joke sealing it, the symbol for the Republic party, etc.).

    The problem with this idea is if we have to skin every human baby, we will have another Moses-mom on our hands that would rather float her baby down the Nile river in a basket than give 'em over to the professionals. There's also the problem of celebrities running off to Africa to have their babies.

    So our two biggest threats to this new classification system working are both with Africa. If giant dinosaurs and monsters like Kong still inhabit those lands, no wonder the people there are still primal. You never hear anybody saying "Peace in the African Congo!" as I'm sure that is even more impossible than would be for the middle-east... I'm sure Africa isn't THAT big of a country, maybe we could get Bush or some other world leader like Kim Yong Wong something, that funny Chinese man on the Team America F-Yeah show, to send in a bunch of troops. Russia is another good choice for sending in a lot of troops. India is another good choice, population-wise, but I can't imagine their people doing much more than teaching Physics 101 or doing my colonoscopies.

    Wait, what were we talking about?

  21. Morphogenesis by SimHacker · · Score: 2

    Collected Works of A.M. Turing
    Morphogenesis
    P.T. Saunders, Editor

    Introduction

    Turing's work in biology illustrated just as clearly as his other work his ability to identify a fundamental problem and to approach it in a highly original way, drawing remarkably little from what others had done. He chose to work on the problem of form at a time when the majority of biologists were primarily interested in other questions. There are very few references in these papers, and most of them are for confirmation of details rather than for ideas which he was following up. In biology, as in almost everything else he did within science -- or out of it -- Turing was not content to accept a framework set up by others.

    Even the fact that the mathematics in these papers is different from what he used in his other work is significant. For while it is not uncommon for a newcomer to make an important contribution to a subject, this is usually because he brings to it techniques and ideas which he has been using in his previous field but which are not known in the new one. Now much of Turing's career up to this point had been concerned with computers, from the hypothetical Turing machine to the real life Colossus, and this might have been expected to have led him to see the development of an organism from egg to adult as being programmed in the genes and to set out to study the structure of the programs. This would also have been in the spirit of the times, because the combining of Darwinian natural selection and Mendelian genetics into the synthetic theory of evolution had only been completed about ten years earlier, and it was in the very next year that Crick and Watson discovered the structure of DNA. Alternatively, Turing's experience in computing might have suggested to him something like what are now called cellular automata, models in which the fate of a cell is determined by the states of its neighbours through some simple algorithm, in a way that is very reminiscent of the Turing machine.

    For Turing, however, the fundamental problem of biology had always been to account for pattern and form, and the dramatic progress that was being made at that time in genetics did not alter his view. And because he believed that the solution was to be found in physics and chemistry it was to these subjects and the sort of mathematics that could be applied to them that he turned. In my view, he was right, but even someone who disagrees must be impressed by the way in which he went directly to what he saw as the most important problem and set out to attack it with the tools that he judged appropriate to the task, rather than those which were easiest to hand or which others were already using. What is more, he understood the full significance of the problem in a way that many biologists did not and still do not. We can see this in the joint manuscript with Wardlaw which is included in this volume, but it is clear just from the comment he made to Robin Gandy (Hodges 1983, p. 431) that his new ideas were "intended to defeat the argument from design".

    This single remark sums up one of the most crucial issues in contemporary biology. The argument from design was originally put forward as a scientific proof of the existence of God. The best known statement of it is William Paley's (1802) famous metaphor of a watchmaker. If we see a stone on some waste ground we do not wonder about it. If, on the other hand, we were to find a watch, with all its many parts combining so beautifully to achieve its purpose of keeping accurate time, we would be bound to infer that it had been designed and constructed by an intelligent being. Similarly, so the argument runs, when we look at an organism, and above all at a human being, how can we not believe that there must be an intelligent Creator?

    Turing was not, of course, trying to refute Paley; that has been done almost a century earlier by Charles Darwin. But the argument from design had survived, and was, and indeed remains, still a potent force in biolog

    --
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  22. In this case, it is a Turing Space by RidiculousPie · · Score: 2, Informative

    A Turing Space rather than a Turing machine. Turing was an excellent mathematician, and although currently most famous for his ideas on computation and the Halting Problem, this was a seperate area of research.

    This area of study (colourations on animals) is based on Reaction Diffusion Equations, of which a canonical example is the Belousov-Zhabotinskii equation derived from a chemical experiment, and a simpler one is the Heat Equation. These take the form of partial differential equations.

    As to simulations of the world or parts on a computer, there is the problem of Heisenberg's Uncertainty Principle, meaning you can never form a complete 'image' of any part of the world.

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    ah, mod points ... now where is my crack?
  23. Re:This should be added to nethack by bmo · · Score: 2, Informative

    Modded troll? Ahahaha, I have metamoderation! Moderator gets spanking!

    This _should_ be seriously added to NH.

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    BMO