DNA computing is a form of computing which uses DNA, biochemistry and molecular biology. A DNA computer has the same basic ability to store information and compute solutions like traditional computers, though its methodology is different as it uses molecular automations and reactions. For example, a DNA computer maybe envisaged as a tiny liquid-based computer comprising DNA in solution. The solution hence uses micro-biology and chemical reactions to compute and process.
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Some attributes and features showing the potential of DNA computers include higher information density, high and strict parallelism, high speed (1018 operations per second) and energy efficiency (1019 operations per Joule).
Evolution and Developments in DNA Computing
In 1994, Leonard Adleman took a simple case of the Directed Hamiltonian Path (DHP) – a problem pertaining to finding valid routes between two selected points on a graph. His approach was to encode each city and each route between two cities in DNA strands, put into a test tube and the combined strands were the possible solutions. He hence filtered the solutions to arrive at a valid result.
A computing device based on DNA can be built in many ways. The computing devices employ basic gates (AND, OR and NOT) and derivates associated with digital logic from a DNA basis. Basically, the logic gates are formed from short strands of DNA and their complementary strands, which in conjunction with some simple molecular machinery mimic their electronic equivalent. Two strands act as the input: each represents a 1 when present or a 0 when absent. The response to their presence or absence represents the output,
which can also be a 1 or 0. Take the “exclusive OR” or XOR logic gate. It produces an output when either of the two inputs is present but not when both are present or both are absent. The gates maybe implemented to make full-fledged processors which are DNA-based.
Advantages of DNA Computing
Computing with DNA offers the advantage of reduction in size and parallelism over conventional silicon-based equipments. Strictly, in silicon-based devices, the operations are time-divided, i.e. operations are continuously processed in parts one after the other, but they are not strictly parallel. In a DNA computer, however, all reactions parallely occur. Adleman, the pioneer of the DNA computer, also mentioned that a single gram of dried DNA is capable of storing the same amount of information as could fit on one trillion CDs. DNA computing also offers much lower power consumption than traditional silicon computers. DNA uses adenosine triphosphate (ATP) as fuel to allow ligation
or as a means to heat the strand to cause disassociation.
Future of DNA Computing
The DNA computer is only in its early stages of development and human interaction is still required to separate the correct answer out by ridding the DNA computer solution of all false answers. This is accomplished through a series of chemical steps. While it is unlikely that DNA computers will be used for tasks like word processing, they may ultimately find a niche market for solving large-scale intractable combinatorial problems such as applications in fuzzy logic and neural networks, elevator management systems and others. The goal of automating, miniaturizing and integrating them into a general-purpose desktop DNA computer may take much longer. However, experts are encouraged by the innate abilities of a DNA computer and see a bright future.
As and when the DNA computer and its models and functionalities develop, there is a chance of a tremendous influx of new intellectual
property being created and registered. Currently big names such as IBM, Lucent Technologies, NEC Corporation and Olympus Corporation, amongst others, have intellectual property pertaining to DNA-based computing.
A quantitative study shows that after the breakthrough work which happened circa 1994, patents pertaining to DNA computing increased rapidly over the years. However, over the past few years, the number of patents filed has reduced. This may be attributed to the fact that certain issues such as building vaster applications and implementation related issues still need to be addressed. Still, there is a huge potential in the domain of intellectual property for DNA computing once these issues are addressed.
(Featured image source: https://en.wikipedia.org/wiki/Molecular_self-assembly#/media/File:Br4Py_self-assembly_on_Au.jpg)