Researching DNA Computation: Questions & Answers

In summary: The advantage of DNA computing is that it is very parallel, which makes it suitable for tasks that are difficult to parallelize.
  • #1
cam875
228
0
I have a problem with DNA computation that is currently being researched. Currently all the research is being done because cells are so parallel but how is that even useful. I keep thinking if you have this so called cell computer calculate every possible addition problem possible for a 32 bit number than what is the point your going to have to still have enough memory to store all the answers and sort through them. I mean its the same with all this quantum computation stuff. Your just going to end up with millions of different answers which you have to sort. Maybe I am just not understanding how cells are parallel and efficient for computation so can someone please enlighten me. Thanks in advance.
 
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  • #2
In a massively parallel system (like DNA computing), the computing nodes themselves are supposed to do the 'sorting'. Suppose each node is checking if its own number divides a given large number. You could then have each node query three neighbors "do you have the answer, or have you heard about the answer?", then repeat a number of times until you can query just a few and find out if the answer is found. You can narrow it down with similar techniques.
 
  • #3
but what if you wanted to add 10110101 to 100001010011, isn't that where current dna computation efforts are behind on. And even if dna can sort itself and all that, you still have to ravage through the results which is where it lacks also according to the articles I have read it took them along time to ravage through the results of the hamiltonian path problem.
 
  • #4
cam875 said:
but what if you wanted to add 10110101 to 100001010011, isn't that where current dna computation efforts are behind on. And even if dna can sort itself and all that, you still have to ravage through the results which is where it lacks also according to the articles I have read it took them along time to ravage through the results of the hamiltonian path problem.

If you wanted to add two (large) binary numbers together there are parallelizable algorithms that don't require as much carrying as the standard 'grade school' algorithm. I don't know how these could be adopted for DNA computation, though.

On the computational power of DNA has a good overview of DNA computing as of last decade. The chart on p. 3 is especially helpful.
 
  • #5
ok but it does seem strange, because it would seem like there is only one way to really add two numbers together and that involves a carry bit and everything just like todays full electronic binary adders do. But thanks for the link there.
 
  • #6
cam875 said:
ok but it does seem strange, because it would seem like there is only one way to really add two numbers together and that involves a carry bit and everything just like todays full electronic binary adders do. But thanks for the link there.

A carry-lookahead adder requires much less carry propagation than the standard ripple-carry adder:
Al Aho and Jeff Ullman, Foundations of Computer Science ch. 13, pp. 716-721.

One way to reduce the number of carry bits for *multiplying* would be the Wallace tree multiplier:
Chris S. Wallace, "A Suggestion for a Fast Multiplier", IEEE Transactions on Electronic Computers EC-13:1 (1964), pp. 14-17.

These require O(log n) carry propagation for n-bit numbers, compared to O(n) for a the usual method.
 
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  • #7
but than it involves you having to multiply, does it not? which is just adding multiple times in a sense or am I confused?
 
  • #8
I'm not in this field... but I hear people talk about DNA computing from time to time. I've always wondered, what's the point? There are plenty of other massively parallel architectures out there which sound much easier to implement. What's the advantage of DNA computing? Or is this something we're doing "just because it's cool"?
 
  • #9
DNA computing is just a curiosity. It suffers from a fundamental problem, and that is of gain. Conventional transistors have gain, which allows the signal to be lifted out of the noise.

No such luck with DNA. They are probably using a roomfull of equipment to read the DNA.
 
  • #10
cam875 said:
but than it involves you having to multiply, does it not? which is just adding multiple times in a sense or am I confused?

A carry-lookahead adder does not require multiplication. I'm not sure if I understand your question...
 
  • #11
Cincinnatus said:
I'm not in this field... but I hear people talk about DNA computing from time to time. I've always wondered, what's the point? There are plenty of other massively parallel architectures out there which sound much easier to implement. What's the advantage of DNA computing? Or is this something we're doing "just because it's cool"?

Smart drug delivery systems, apparently, seem to be the goal of the research.
 
  • #12
kingdomof said:
Smart drug delivery systems, apparently, seem to be the goal of the research.

ah, of course, that makes sense. Thanks!
 

Related to Researching DNA Computation: Questions & Answers

1. What is DNA computation?

DNA computation is a field of research that explores the use of DNA molecules as a medium for information processing and storage. It involves manipulating and controlling the chemical reactions of DNA to perform computational tasks.

2. How does DNA computation work?

In DNA computation, DNA molecules are used to represent and store data. By manipulating the DNA sequences and their interactions, researchers can perform calculations and solve problems. This is done through biochemical reactions, such as DNA hybridization and enzymatic cleavage.

3. What are the advantages of DNA computation?

Some potential advantages of DNA computation include its massive parallel processing capabilities, high storage density, and low energy requirements. It also has the potential for faster and more efficient computing compared to traditional silicon-based computers.

4. What are the challenges of DNA computation?

There are several challenges that need to be addressed in DNA computation, such as the cost and complexity of synthesizing and manipulating DNA molecules, and the potential for errors in the biochemical reactions. There are also ethical considerations surrounding the use of DNA for computing purposes.

5. What are the potential applications of DNA computation?

DNA computation has a wide range of potential applications, including data storage, cryptography, and bioengineering. It could also have implications in fields such as medicine and biotechnology, as well as in developing new computing technologies.

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