2. Overview
Introduction to DNA
What is DNA computing
Adleman’s Hamiltonian path problem.
Cutting Edge Technologies
Pros and Cons
DNA Vs Electronic Computers
Conclusion
3. What is DNA?
• DNA stands for Deoxyribonucleic Acid
• DNA represents the genetic blueprint of living
creatures
• DNA contains “instructions” for assembling
cells
• Every cell in human body has a complete set
of DNA
• DNA is unique for each individual
4. Double Helix
• “Sides”
Sugar-phosphate backbones
• “ladders”
complementary base pairs
Adenine & Thymine
Guanine & Cytosine
• Two strands are held together by
weak hydrogen bonds between the
complementary base pairs
• Thats the picture of human DNA
5. Uniqueness of DNA
Why is DNA a Unique Computational Element???
• Extremely dense information storage.
• Enormous parallelism.
• Extraordinary energy efficiency.
6. Dense Information Storage
This image shows 1 gram of
DNA on a CD. The CD can hold
800 MB of data.
The 1 gram of DNA can hold
about 1x1014 MB of data.
The number of CDs required
to hold this amount of
information, lined up edge to
edge, would circle the Earth 375
times, and would take 163,000
centuries to listen to.
7. Storeing info inside DNA
The following technique use for
copying,sorting,concating and spliting info into DNA
module
• ligation,
• hybridization,
• polymerase chain reaction (PCR),
• gel electrophoresis, and
• enzyme reaction.
8. Steps of DNA computing
Encodind schame
Ligation and hybridization
Polymerase Chain Reaction (PCR)
Affinity Separation
Gel Electrophoresis
9. Encoding schame
Encode each object of interest into DNA sequence
A correct design is necessary
Incorrect design can make the system incorrect
10. Ligation and hybridization
The sequence when DNA drop in a test tube using a
micro pipattor
DNA sequences recombine with each other by means
of some enzymereaction, this process being referred to
as ‘ligation’
. All DNA sequences to be used in the experiment are
mixedtogether in a single test tube.
is heated to 95o centigrade (celsius) and cooled to
20oC at 1oC per minutefor hybridization
12. Polymerase chain reaction
. Initialization: a mix solution of template, primer, dNTP and enzyme
isheated to 94 − 98◦C for 1 − 9 minutes to ensure that most of the
DNAtemplate and primers are denatured.
. Denaturation: heat the solution to 94 − 98◦C for 20 − 30 seconds
forseparation of DNA duplexes
Annealing: lower the temperature enough (usually between 50−64◦C)
for20−40 seconds for primers to anneal specifically to the ssDNA
template.
Elongation/Extention: raise temperature to optimal elongation
temperatureof Taq or similar DNA polymerase (70 − 74◦C) for the
polymeraseadds dNTP’s from the direction of 5_ to 3_ that are
complementary to thetemplate;
. Final Elongation/Extention: after the last cycle, a 5 − 15 minutes
elongationmay be performed to ensure that any remaining ssDNA is
fullyextended
Step 2 to 4 is repeated for 20−35 times called thermal cycler.
13. Affinity saparation
Varify each of data include acertain sequinence or not
process a double stranded DNA is incubated with the
Watson-Crick complement of data that is conjugated
to magnetic beads
. Abead is attached to a fragment complementary to a
substring then a magneticfield is the used to pull out
all of the DNA fragments containing suchsequence.
The process is then repeated
15. Gel electrophoresis
charged molecules to move in an electric field
Basically, DNA molecules carry negative charge.Thus, when
we place them in an electrical field, they tend to migrate
towardsa positive pole.
Since DNA molecules have the same charge per unit
length,they all migrate with the same force in an
electrophoresis process. Smallermolecules therefore
migrate faster through the gel, and can be sorted
accordingto size (usually agarose gel is used as the medium
here).
At the end of thisprocess the resultant DNA is
photographed
16. How enormous is the
parallelism?
• A test tube of DNA can contain trillions of
strands. Each operation on a test tube of DNA is
carried out on all strands in the tube in parallel !
• Check this out……. We Typically use
17. How extraordinary is the
energy efficiency?
• Adleman figured his computer was running
2 x 1019 operations per joule.
18. Can DNA compute?
DNA itself does not carry out any computation. It
rather acts as a massive memory.
BUT, the way complementary bases react with
each other can be used to compute things.
Proposed by Adelman in 1994
19. DNA COMPUTING
A computer that uses DNA (deoxyribonucleic
acids) to store information and perform complex
calculations.
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.
20. Adleman’s Experiment
• Hamilton Path Problem
(also known as the travelling salesperson problem)
Perth
Darwin
Brisbane
Sydney
Alice Spring
Melbourne
Is there any Hamiltonian path from Darwin to Alice Spring?
21. Adleman’s Experiment
• Solution by inspection is:
Darwin Brisbane Sydney Melbourne Perth
Alice Spring
• BUT, there is no deterministic solution to this
problem, i.e. we must check all possible
combinations.
Perth
Darwin
Brisbane
Sydney
Alice Spring
Melbourne
22. Adleman’s Experiment
1. Encode each city with complementary base -
vertex molecules
Sydney - TTAAGG
Perth - AAAGGG
Melbourne - GATACT
Brisbane - CGGTGC
Alice Spring – CGTCCA
Darwin - CCGATG
23. Adleman’s Experiment (Cont’d)
2. Encode all possible paths using the
complementary base – edge molecules
Sydney Melbourne – AGGGAT
Melbourne Sydney – ACTTTA
Melbourne Perth – ACTGGG
etc…
24. Adleman’s Experiment (Cont’d)
3. Merge vertex molecules and edge molecules.
All complementary base will adhere to each other to
form a long chains of DNA molecules
Solution with
vertex DNA
molecules
Solution with
edge DNA
molecules
Merge
&
Anneal
Long chains of DNA molecules (All
possible paths exist in the graph)
25. Adleman’s Experiment (Cont’d)
• The solution is a double helix molecule:
Darwin Brisbane Sydney Melbourne Perth Alice Spring
CCGATG – CGGTGC – TTAAGG – GATACT – AAAGGG – CGTCCA
TACGCC – ACGAAT – TCCCTA – TGATTT – CCCGCA
Darwin
Brisbane
Brisbane
Sydney
Sydney
Melbourne
Melbourne
Perth
Perth
Alice Spring
26. Operations (Cont’d)
• Merging
mixing two test tubes with many DNA molecules
• Amplification
DNA replication to make many copies of the original
DNA molecules
• Selection
elimination of errors (e.g. mutations) and selection of
correct DNA molecules
27. THE FUTURE!
Algorithm used by Adleman for the traveling salesman
problem was simple. As technology becomes more
refined, more efficient algorithms may be discovered.
DNA Manipulation technology has rapidly improved in
recent years, and future advances may make DNA
computers more efficient.
The University of Wisconsin is experimenting with
chip-based DNA computers.
28. DNA computers are unlikely to feature word
processing, emailing and solitaire programs.
Instead, their powerful computing power will be used
for areas of encryption, genetic programming,
language systems, and algorithms or by airlines
wanting to map more efficient routes. Hence better
applicable in only some promising areas.
31. The Smallest Computer
• The smallest programmable DNA computer was
developed at Weizmann Institute in Israel by Prof.
Ehud Shapiro last year
• It uses enzymes as a program that processes on 0n
the input data (DNA molecules).
32. Pros and Cons
+ Massively parallel processor
DNA computers are very good to solve Non-deterministic
Polynomial problems such as
DNA analysis and code cracking.
+ Small in size and power consumption
33. Pros and Cons (Cont’d)
- Requires constant supply of proteins and
enzymes which are expensive
- Errors occur frequently
a complex selection mechanism is required and
errors increase the amount of DNA solutions
needed to compute
- Application specific
- Manual intervention by human is required
34. DNA Vs Electronic computers
At Present, NOT competitive with the state-of-the-art
algorithms on electronic computers
Only small instances of HDPP can be solved.
Reason?..for n vertices, we require 2^n molecules.
Time consuming laboratory procedures.
Good computer programs that can solve HSP for
100 vertices in a matter of minutes.
No universal method of data representation.
35. Conclusion
• Many issues to be overcome to produce a
useful DNA computer.
• It will not replace the current computers
because it is application specific, but has a
potential to replace the high-end research
oriented computers in future.
• Recently its use in elevator system.
