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Biotech Science

Modeling the Building Blocks of Life 59

Posted by Zonk from the hard-not-to-enjoy-emulation dept.
eldavojohn writes "A new research paper is creating some buzz about the roles of computer engineering in biology. Historically, computational techniques in genome sequencing have proved useful in predicting which DNA sequence produces which amino acid and which amino acid sequence produces which protein. Now, this new research is leading towards a robust model of proteins and their messaging systems. This is one step further in understanding the basics of life and, consequently, pushes us closer to being able to emulate organisms entirely from the bottom up instead of our failed prior approaches of from the top down. A long way from perfect, but an opening into a wide field of study and maybe even a new division of biology."
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Modeling the Building Blocks of Life More

Modeling the Building Blocks of Life

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  • Cool! (Score:3, Funny)

    by jfade ( 1096961 ) on Friday May 18, 2007 @01:49PM (#19181733)
    So will this someday allow me to take parts from various trees and make a whole new species of tree? I think I'll call it "Frankenpine..."
  • Computer geeks studying simulated vulval development.

  • Hmmm.... (Score:5, Insightful)

    by Otter ( 3800 ) on Friday May 18, 2007 @01:50PM (#19181757) Journal
    C. elegans has a completely predictable sequence of cell division, which is one of the main reasons (along with transparency, self-fertilization, survival in a freezer and some others) why it's so heavily studied.

    This is a really nice piece of work, but they picked some really low-hanging fruit to try out their method. Which is one of the hallmarks of really nice work, of course.

    • Re:Hmmm.... (Score:4, Informative)

      by daniorerio ( 1070048 ) on Friday May 18, 2007 @02:56PM (#19182793)
      you think so? How many animals are really studied do you think? I can give you the answer: C. elegans, fruitfly, zebrafish, bulfrog, chicken, mice and rats. The rest hardly counts. The reason why they choose C. elegans in this case you already stated, the principles of signal transduction apply just as much to human beings as to those worms. Your EGFR/RAS/MAPK pathway isn't that different...

      • Re: (Score:1)

        by Otter ( 3800 )
        Your EGFR/RAS/MAPK pathway isn't that different...

        No, but its effects are much, much noisier. I'd be very surprised if they could get a result like this in your namesake.

        • True, but obviously you choose a simple model as a proof of concept, and work from there.
          • No offence, I find it odd your first reply started with "you think so? How many animals are really studied do you think?", yet you seem to be in complete agreement with everything that is actually in both of Otter's posts?

            BTW: I think you need to add rabbits, pigs, sheep, cows, horses, goats and humans to your list.
  • Comment removed based on user account deletion

  • Emulate Life? (Score:3, Funny)

    by AbsoluteXyro ( 1048620 ) on Friday May 18, 2007 @01:51PM (#19181775)
    Emulate Life, huh? These boys are playing catch-up. Will Wright has been on this one for a while now.

  • Engineered dragons. (Score:1, Interesting)

    by Anonymous Coward
    Then we can make programs to engineer a dragon.
    I think custom programs like this are the upitamy of computational biology.
    It is cool to think about how you would store the information to make a bone with a certain curve.
    I'm sure there are huge interdependancies in the system but... we can just punch it in the
    computer and see if it works none of that aliens 3 shit!
    I want to hear more about organic ships.

  • Computer Science not Computer Engineering (Score:5, Informative)

    by kramer2718 ( 598033 ) on Friday May 18, 2007 @01:57PM (#19181895) Homepage
    This may be a bit picky, but the work being done here is not computer engineering but rather computer science. Computer engineering generally refers to engineering techniques for building computers and computer systems (including parts of electrical engineering, materials science, algorithms, etc.) whereas computer science is the study of algorithms. This work is not designing computing systems but rather using algorithms to model the building blocks of biology.
    • That comment is obligatory, not picky. It's also spot on, of course.
    • Usually when computers and numerical modeling techniques are used to understand and solve problems in sciences the term we use is computational. Using computers in fulid mechanics, it is computational fluid mechanics. Similarly there are computational electromagnetics, computational solid mechanics (usually finite element methods) computational geometry etc. So in that way, the correct term here would have been, "computational biology".

      • Re: (Score:3, Informative)

        by PresidentEnder ( 849024 )
        How about bioinformatics [wikipedia.org]?
        • The cited Wikipedia article starts with an implication that bioinformatics and "computational biology" are synonymous.
          • Yes, but it says later that while they are often treated as synonymous, they are different. Computational means that we're using computers to study , within the classical scientific method: hypothesize, test, observe, refine, grant money, ???, profit (except that we have to use a computer somewhere). Bioinformatics is more about modeling things inside the computer, and doesn't have any real-world parts: your bacteria/proteins/virii exist only as bits. If you use the terms interchangeably nobody will think
        • BioWare
    • It opens the doors to designing biological machines from the ground up to perform specific tasks.

       
  • In respect to antibiotics and finding medicine to help cure virus related illnesses. We could virtually create them at the atomic level, shove it onto a HUGE grid and let the parallized life emualtor permutate the genetic code and see how different genes effect the organism and it's environment. While this sounds to cpu intensive for higher organism, I can see this being done on smaller single-cell forms of life.

    • Re:Useful in medicine (Score:4, Interesting)

      by CogDissident ( 951207 ) on Friday May 18, 2007 @02:04PM (#19181997)
      Heck, if we could create a self propegating virus with a near-nil chance of mutation, that could specifically target and destroy another virus (ie: aids killing virus), we could wipe out entire strains of it. And if the facilities could model it at the most basic levels, the computer could simulate purposefull mutations (disable the self-kill genes) and try to find a combination that works against the next kind of mutation.

      Also very usefull for producing hard-to-make chemicals, as we could create custom-made bacteria that churn out the protein sequence we want. We already do this in a lot of cases, but making the base bacteria is very difficult, and a steamlined method to make different kinds of chemicals could be a huge help for everyone involved.
      • [blockquote]near-nil chance of mutation[/blockquote] If we're designing this to work inside the human body (why would we want to eradicate viruses anywhere else?) then it would need to keep from triggering our immune systems. Any mutation which leaves the invisibility aspect intact would make this a very dangerous little bug, indeed. Near-nil isn't good enough. Besides, how are you going to keep it from mutating? DNA is little and thus easy to hork around with.
        • Well, the current way our own blood keeps from mutating is the fact that we have several different genes that all say "if this cell mutates, kill it, kill it with fire". The only way for our cells to mutate is for "all" of these different genes to turn off, simultaniously, and then then, a small percentage of these cells lose their growth inhibitor, and thats called cancer.

          Considering the amount of blood in our systems, and the chances of cancer per-cell, if we, i don't know, lets say mutiply the number o
      • > that could specifically target and destroy another virus (ie: aids killing virus)

        I agree with the theory, but you probably want to destroy HI-virus. Aids "is a collection of symptoms and infections resulting from the specific damage to the immune system caused by the human immunodeficiency virus (HIV)."
        http://en.wikipedia.org/wiki/Aids [wikipedia.org]

      • Re: (Score:3, Interesting)

        by smellsofbikes ( 890263 )
        If you want chemical farms, rather than make a whole bacterium, why not just make the enzyme or enzyme train that produces the chemical from a set of precursors, and then stick those into the DNA of a given bacterial species, in a sequence that will be strongly expressed? That's what we've been doing since the '80's, in bacteria and in animals. A friend of mine designed a cow that produced interferon in the cow's milk when fed zinc-rich foods, and it worked. Now, interferon isn't a new chemical. But the

      • Re: (Score:1, Informative)

        by Anonymous Coward
        Interesting idea but I would reserve a few questions for such a proposition. First of all, how would you create a virus that doesn't mutate? Viruses that go through the lysogenic cycle(AIDS for example), by definition incorporate into host DNA to hijack the processes of cellular protein production. This is an inherently mutation prone process especially during separation from host DNA. I suppose adding an error checking protein functionally comparable to some polymerases for dna replication would be possibl

        • Re: (Score:3, Informative)

          by CTachyon ( 412849 )

          A mutation-resistant virus is easy enough. dsDNA viruses are quite stable, and most of them function by adding their own chromosomes to the nucleus, without altering the host DNA. The result is that they rely on the same DNA polymerase and proofreading enzymes that the cell uses for its own replication. The poxviruses, for instance, are a reasonable template for fashioning an HIV counter-virus, as they generally replicate in this manner.

          One major challenge would be figuring out how to reliably recogniz

      • Since when do viruses "target and destroy" other viruses?
        • Well, right now we have viruses that target and destroy certain kinds of cells (going back to the HIV/aids example of destroying white blood cells). Its not hard to imagine reprogramming one to target other viruses.

    • Re: (Score:1)

      by odbasta ( 993741 )

      CPU intensity will not be an issue very, very soon. Think about it...when scientists first started sequencing the human genome, they only completed a very small (something like) 0.1% in the first year. Many people doubted that it could be completed in the 10 year timeline of the project. But, given that computing power was (and still is) increasing exponentially, the majority of the sequencing was easily completed in the final years.

      Many people (including slashdotters) take a linear view of technology,

  • Nothing special... (Score:3, Insightful)

    by voislav98 ( 1004117 ) on Friday May 18, 2007 @02:04PM (#19181999)
    If you read the actual article, it's nothing special. They took what's known from extensive lab studies of this organism and made a computer model out of it. It's not really able to predict how the organism would behave under some unknown conditions, but it has some mechanism biult in that would, kind of, wink, wink, give it that capability. What is the most telling is that they hadn't been able to predict the behaviour of one of their cell lines (lin-15(lf) mutants), so it just shows how limited the model is. The annoying thing is that the press article is barely readable from all the buzz words and other crap, sounding like it's some sort of breakthrough, when it's just run-of-the-mill stuff done in probably a dozen other places.
    • Just because it isn't the first of its kind doesn't mean it's not special. Computer modelling gives a whole new level of detail on development processes - it's like moving from a light microscope to an electron microscope. It can allow us to vibrantly integrate large amounts of data and move from reductive to synthetic biology. In this case, it has allowed the researches to see the timing of the chemical signals cells send each other to cause them to develop. This information is going to be crucial for gett
      • Don't get me wrong it's good research, but it's no different or no more advanced than work by another dozen research groups (I could probably name a few). The only difference is that others don't get their articles on /.
  • This reminds me of the movie, The Thirteenth floor.

    If you could simulate the building blocks of life in a virtual life, could you not also accelerate the evolution process and create sentient life? If all life truly started from these base chemical reactions, then it should be possible, technology willing, to create virtual life.
  • I'm waiting for the day when I can create my own little life forms and have the computer model it in real-world scenarios. Imagine being able to watch evolution happen right before your very eyes! It would be like playing spore but more realistic!

  • Interesting project, old idea (Score:4, Informative)

    by comp.sci ( 557773 ) on Friday May 18, 2007 @03:25PM (#19183181)
    While this project might be interesting to some, this is hardly a new approach to biology.
    Computational Biology has been around for quite a while now and simulation is actually one of its strongest points so far.
    There used to only be two main settings for conducting experiments: in vitro (outside of living organisms, literally within a glass) and in vivo (done in living tissue/organisms).
    With the advent of comp. bio., a new and comparatively incredibly inexpensive way of experimenting has become available: in silico (experiments are simulated) This is pretty much what the article was talking about and has been a massive success in biology, for quite some time now!
    Since this term has been used since the 1990s, this is not exactly new.

    I won't even go into talking about the misleading /. summary, but it does not really give the reader a good idea of the current state of the HUGE field of computational biology!

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