How DNA Computers Will Work
DNA (deoxyribonucleic acid) molecules, the material our genes are made of, have the
potential to perform calculations many times faster than the world's most powerful
human-built computers. DNA might one day be integrated into a computer chip to
create a so-called biochip that will push computers even faster. DNA molecules have
already been harnessed to perform complex mathematical problems.
In 1994, Leonard Adleman introduced the idea of using DNA to solve complex
mathematical problems. Adleman, a computer scientist at the University of Southern
California, came to the conclusion that DNA had computational potential after reading
the book "Molecular Biology of the Gene," written by James Watson, who co-discovered
the structure of DNA in 1953. In fact, DNA is very similar to a computer hard drive in
how it stores permanent information about your genes.
Adleman is often called the inventor of DNA computers. His article in a 1994 issue of
the journal Science outlined how to use DNA to solve a well-known mathematical
problem, called the directed Hamilton Path problem, also known as the "traveling
salesman" problem.
The goal of the problem is to find the shortest route between a number of cities, going
through each city only once. As you add more cities to the problem, the problem
becomes more difficult. Adleman chose to find the shortest route between seven cities.
Here are the steps taken in the Adleman DNA computer experiment using his DNA
test-tube computer:
 Strands of DNA represent the seven cities.
 In genes, genetic coding is represented by the letters A, T, C and G.
 Some sequence of these four letters represented each city and possible flight
path.
 These molecules are then mixed in a test tube, with some of these DNA strands
sticking together.
 A chain of these strands represents a possible answer.
 Within a few seconds, all of the possible combinations of DNA strands, which
represent answers, are created in the test tube.
 Adleman eliminates the wrong molecules through chemical reactions, which leaves
behind only the flight paths that connect all seven cities.
The success of the Adleman DNA computer proves that DNA can be used to calculate
complex mathematical problems. However, this early DNA computer is far from
challenging silicon-based computers in terms of speed. The Adleman DNA computer
created a group of possible answers very quickly, but it took days for Adleman to
narrow down the possibilities. Another drawback of his DNA computer is that it
requires human assistance. The goal of the DNA computing field is to create a device
that can work independent of human involvement.
Tube test with details
We create test tubes that have many multiples of the strands representing each edge
and each vertex. Once these tubes are mixed together, legal paths through the graph
are generated by the mutual attraction of strings and their complements by hydrogen
bonding. For example, take the graph shown in figure .
Since this example has six vertices and the DNA alphabet only contains the letters A,
T, C, and G, it is necessary to have each
vertex represented by at least two
characters. We expand this to eight
characters in order to avoid the problem of
long common sub-strings, and denote each
vertex by a DNA strand as listed in table .
The edges, furthermore, are represented as in table .
Vertex
DNA Strand
Edge
DNA Strand
A
ATCGAGCT
A -> B
TCGAACCT
B
TGGACTAC
B -> C
GATGCTCT
C
GAGACCAG
C -> D
GGTCGCTA
D
CGATGCAT
D -> F
CGTACGAT
E
AGCTAGCT
F -> E
CTGATCGA
F
GCTAGACT
E -> F
TCGACGAT
E -> A
TCGATAGC
E -> B
TCGAACCT
B -> F
GATGCGAT
We can now see that, given this representation, strands representing vertex A in a test
tube will tend to pair with strands representing edges of the form A -> x. Because of
this tendency to pair, one can construct all paths through the graph by simply producing
large quantities of each of the strands listed in table and mixing them together. Other
environmental conditions must be met so that the pairing process takes place as
intended, but those details will be left for later discussions.
Once all of the legal paths are constructed, finding a solution (if one exists) to the
instance of HP is equivalent to finding a double-stranded DNA sequence that contains
exactly one copy of the strands representing each vertex. This search can be
performed using methods from molecular biology. Moreover, each of steps (including
the synthesis of the paths) could be performed in linear time and thus the entire
algorithm can be executed in linear time.
To Adleman, the following advantages of DNA computing became evident;
Speed – Conventional computers can perform approximately 100 MIPS (millions of
instruction per second). Combining DNA strands as demonstrated by Adleman, made
computations equivalent to 10 9 or better, arguably over 100 times faster than the
fastest computer. [5] The inherent parallelism of DNA computing was staggering.
Minimal Storage Requirements – DNA stores memory at a density of about 1 bit per
cubic nanometer where conventional storage media requires 1012 cubic nanometers to
store 1 bit. [5] In essence, mankinds collective knowledge could theoretically be stored
in a small bucket of DNA solution.
Minimal Power Requirements - There is no power required for DNA computing while the
computation is taking place. The chemical bonds that are the building blocks of DNA
happen without any outside power source. There is no comparison to the power
requirements of conventional computers.
There have been other researchers since Adlemans work that have demonstrated
similar possibilities of DNA computing.
For example a group of researchers at
Princeton in early 2000 demonstrated an RNA computer similar to Adleman’s which had
the ability to solve a chess problem involving how many ways there are to place knights
on a chess board so that none can take the others.
Adleman instantly envisioned the use of DNA computing for any type of computational
problems that require massive amounts of parallel computing. As his background
stemmed from computer encryption, he particularly envisioned DNA computing in
helping create and decipher algorithms in the field of cryptography. The possibility
existed of the very genetic makeup of an individual being used in the
encryption/decryption of data from/to that person. The possibility was also seen that
the DNA of an individual will give them the ‘who you are’ portion of the ‘who you are’,
‘what you know’, ‘what you have’ aspects of security authentication.
There has been much speculation of the use of this type of technology for
cryptographic and steganographic means that would take advantage of the parallel
computation possibilities available with DNA computing. Are these real possibilities for
the security industry or are the processes involved in its implementation too difficult to
envision in the immediate future? Next we will examine DNA computing within these
security applications to determine the likelihood of DNA being used in their
advancement.