An Introduction to DNA Computing.
                     AN INTRODUCTION TO 
DNA COMPUTING
DNA Computing
• DNA computing, the performing of computations using biological molecules, rather 
than traditional silicon chips. 
• The idea that individual molecules could be used for computation dates to 1959, 
when American physicist Richard Feynman presented his ideas on nanotechnology.
Source: www.britannica.com
APPLICATIONS OF DNA COMPUTING
Security
• Deploying DNA algorithms in cryptography to build an intrusion detection model is 
the most recent development. 
• The ability to store 108 terabytes of data in 1 gram of DNA has led to the potential 
holding a huge one-time pad.
Source: www.section.io
Scheduling
• DNA algorithms are used to work out elevator schedule systems and rearrangement 
of Flexible Manufacturing System. 
• However, due to a lack of theoretical base, only medium-sized tasks were taken into 
consideration.
Source: www.section.io
Clustering
• DNA- based clustering involves using strands to assign edges and vertices. Iterative 
calculations are performed for every produced cluster to improve quality.
Source: www.section.io
OPERATIONS ON DNA COMPUTING
Synthesis
• We can use a machine to create a bunch of single DNA strands of any string we like. 
The technical term for these is oligonucleotides, but they’re just short DNA pieces.
• One limitation is we can only make strands of 20-25 nucleotides with current lab 
techniques.
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Amplify
• Given a test tube with only a few strands of DNA, we can amplify them into millions 
of strands using a process called polymerase chain reaction (PCR).
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Extract pattern
• Given a test tube of DNA, we can extract only those that contain a given pattern as a 
substring. 
• To do this, put the complement of the pattern string into the solution and cause it to 
anneal. Only strands that contain the pattern will anneal, and the rest can be 
washed away.
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Limitations of DNA Computing
• Each operation takes hours of lab work. This is not really a fundamental problem; in 
the future we might use robots to automate these lab operations.
• The biggest barrier to solving large instances is that right now, we can’t synthesize 
arbitrary long strands of DNA (oligonucleotides). 
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Advantage of DNA Computing
• The use of DNA strands to compute has led to high parallel computation that makes 
up for the slow processing of the chip. 
• Memory space required by DNA is around 1 bit per cubic nanometer which is much 
less when compared to regular storage systems Consumption of power is almost nil 
as the chemical bonds in DNA produce energy to build or repair new strands. 
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