DNA Computing

What is it?  “DNA computing is a branch of computing which uses DNA, biochemistry, and molecular biology hardware, instead of the traditional silicon-based computer technologies.”  The idea of molecular computing dates all the way back to 1959, when Richard Feynman presented ideas on nanotechnology. However, there were no physical results until 1994 when a paper was published showing how molecules could solve computational problems, specifically the Hamiltonian Path Problem.

Why is DNA better than what we’re using now?  In short, we’re always trying to find ways to make computers smaller and faster. (Moore’s Law).  Silicon chips will eventually reach a point where they can’t be reasonably made more efficient. This is where DNA comes in.  There are two main branches of how this can be used: Molecular structures as storage devices, and molecular structures as processors.

DNA as Storage  Because of the way DNA is sequenced, computers can actually read the individual chemical strands and translate them into binary.  (49 sec)

DNA as a Processor  Using DNA as a processor started with the Hamiltonian Path Problem in 1994, but the prospects for what it’s capable of are much greater.  Current work has focused on using these processors to solve NP-complete problems. That is, problems where as the complexity increases the time it takes to complete them increases at an exponential rate. It’s not even known at this time whether they can be solved in polynomial time.  The biggest advantage of using DNA processors is that computations can be run in parallel, which makes them run much faster. This means that they could run complex simulations that current technology simply can’t, such as quantum computing.

Current Capabilities  Researchers have already made what is essentially a DNA hard drive. They’ve been able to sequence strands to record Shakespeare’s sonnets, MLK’s “I have a Dream” speech, a photo of their lab, and research papers onto one strand of DNA. They then were able to make a computer play all of it back for them.  All of the data transmitted over the internet over the course of a month could fit into two pounds of sequenced DNA.  While all of this sounds amazing, it does cost about $20,000 or so to sequence the DNA required to store even a small amount of data.

Future Capabilities  As discussed, the prospect of using DNA to process data could be used to solve exceptionally complex math. Because it runs in parallel, these processors could be amazingly fast.  When computers start using the same basic building blocks as humans, it could open up new possibilities for computer intelligence, such as associative memory.  Because computer scientists will have to work closely with other branches of science when it comes to sequencing DNA, it could lead to other advances, too.  These advances could lead to medicine personalized to each individuals genetic code.

Risks  Because of how much data can be stored in a very small amount of space, once this type of storage becomes more cost effective, it could lead to more collection of user data.  One definite future risk of DNA processing would be the capability to run massive computations in parallel, which would greatly hinder current cryptography methods.

Resources  of-dna-based-computing.html of-dna-based-computing.html  