Convergence of Biology and Computers?
Pankaj Arora asks: "This summer I am working on both Bioinformatics and Molecular Biology research projects at the Mayo Clinic Rochester. Being an MIS major with a heavy CS background, I've been learning about biochemistry performing polymerase chain reactions (PCRs) and RNA retranslation among other things. I've learned biology works a lot like computers; binary has 1s and 0s, DNA has nucleotides: A, T, C, and G. Binary has 8 bits to a byte, DNA has 3 nucleotides to a codon. Computers and biology seem to have a natural fit; information is encoded and represented 'digitally' in a sense. I was wondering what people thought about the future of biology-based and genetics-based computing due to the immense efficiencies that lie in nature. This has been discussed to an extent here, but there were some specific aspects that I feel are quite important and were not discussed thoroughly, thus I have a few questions to pose to the Slashdot community."
"The aspects I would like discussed are as follows:
- In the long run, will biology rewrite computing or will modern day technology concepts and theory be integrated into biology? If both are true, which will have the greater effect? I understand long run is ambiguous in this question, but Iâ(TM)m interested in all thoughts using any applicable definition.
- Tied to the first question: How will the nature of computing, and how we perceive it, change due to biology integration? More to the point, how much of the theory we learn today may change?
- What will be the biggest issue determining the success of the adoption of biology-integrated computing? Will it be technology factors or will it be societal factors (e.g., rebellion by the Right Wing), or something else? What things must hold true to make the idea succeed?
- And perhaps the hottest issue of all: Is there anything inherently wrong with pursuing this avenue? What may be some of the consequences?
(I have an insulin pump) It really hasn't changed my life much yet. Still have to program the thing, refill it, etc. Maybe one day when it's internal and self-regulating, but for now, it's a fancy needle/pda.
it all boils down to this:
;)
binary + DNA = phi
(try and figure that one out
We're like rats, in some experiment! -- George Costanza
Godel, Escher, Bach talks all about the overlaps and comparisons between biology and computers. In particular, Hofstadter details a one-to-one correspondence from the Central Dogma to Godel's Incompleteness Theorem. It's dense, but it's great stuff.
GET YOUR WEAPONS READY! --DR.LIGHT
As one of the chosen few attempting to understand the fundamentals of protein folding, I can say that we are still a long way off from understanding how these "few" 20 amino acids fold into highly-specific structures. There are people with access to super computing centers (ala: UCSD super computing center, IBM's Gene Blue) who still cannot devise a simulation that accurately reproduces biological systems. The amount of atomic and subatomic properties that must be taken into account is just overwhelming. It can take a 64cpu cluster of computers a week to reproduce what nature does in 1 nanosecond!
So how can we restructure our current computing system to a model that is based upon something that we understand only at basic level? We can't. While I agree that a biologically-derived computing architecture could be quite powerful indeed, we are still a LONG way off from the level of understanding needed to even put this idea on the drawing board.
If I can do a slightly different interpretation of the questions being asked - can biology inspire changes in computing? The answer is yes - it already has. Many of our ideas of aritificial intelligence or computer learning have come from neural network-type studies of brain structures. At some point, the equivalent circuit in silicon may precisely reproduce what the neuron is doing. Aside from the time issue (nerve conduction is blazingly fast), you would serve your function staying in silicon.
I'm an aspiring computational ecologist, majoring in biology, minoring in CS. (for the uninformed- ecology != environmentalism or anything of that sort) I'm in Minnesota, although at the other end of the state.
I don't think biology will rewrite CS. It will influence it, for sure, but there isn't anything fundamentally different between a biological solution and a technological one. I think as we learn more of the bigger picture in various biological fields, when we truly understand it, we will integrate that knowledge into applied CS. We've been reading the book for some time now, but we really don't know enough about the subject matter to really apply it.
I think there is a lot of use for biomimicry in computing. I think integration of biological elements into our computers is quite a bit far off and perhaps a bit sci-fi-ish for now, but taking ideas (algorithm would often be an understatement) that work well in biological systems and using them in computing is something we can do now with some success.
Working toward a usable PDA environment in the spirit of Newton OS: Dynapad
What I'm listening to now on Pandora...
DNA in and of itself can't do calculations (well, that I know of... show me how and I'll believe you). The brain can do massively parallel computations (think facial/object/voice recognition in microseconds, and at the same time). Here's one big problem in taking advantage of that kind of thing (other than ethical issues). Say you have taken some head and hooked it up to a computer. It may recognize things just fine and many times faster than any normal computer, but how to get that information back to the computer? Sure you can interface with specific neurons, etc. but which ones? Do you tap into Wernicke's or Broca's area (the parts responsible for speech/word comprehension)? How do you interpret the signals coming from that area? If you interface anywhere else, you likely wouldn't have any kind of word/name/etc, because Wernicke's is responsible for all speech comprehension (without it there's no giving meaning to the words one hears or reads, and no putting words to actions, feelings, anything else).
So what biological computing has to offer in speed is basically countered by the difficulty in gaining access to the information, unless MAJOR advances are made. And for simple math-type computing problems, biological processing would probably never catch up to what we have now in electronic computers.
Just my 2 bits worth.