In 1994, University of Southern California computer scientist Leonard Adelman suggested that DNA could be used to solve complex mathematical problems. Adelman found a way to harness the power of DNA to solve the Hamiltonian path problem (the traveling salesman problem), whose solution required finding a path from start to end going through all the points (cities) only once.
Each city was encoded as its own DNA sequence (DNA sequence consists of a series of nucleotides represented by the letters A, T, G, C).
The DNA sequences were set to replicate and create trillions of new sequences based on the initial input sequences in a matter of seconds (called DNA hybridization). The theory holds that the solution to the problem was one of the new sequence strands. By process of elimination, the correct solution would be obtained.
Adelman’s experiment is regarded as the first example of true nanotechnology.
The main benefit of using DNA computers to solve complex problems is that different possible solutions are created all at once. This is known as parallel processing. Humans and most electronic computers must attempt to solve the problem one process at a time (linear processing). DNA itself provides the added benefits of being a cheap, energy-efficient resource.
In a different perspective, more than 10 trillion DNA molecules can fit into an area no larger than 1 cubic centimeter. With this, a DNA computer could hold 10 terabytes of data and perform 10 trillion calculations at a time.