DNA computing is a novel approach that uses DNA, RNA, and biochemical reactions to solve computational problems. The document outlines Adleman's experiment using DNA to solve the Hamiltonian path problem. It then discusses applications of DNA computing such as solving NP-complete problems, data storage, DNA sequencing, and mutation detection. Finally, it compares DNA computers to conventional computers, noting DNA's ability to perform massive parallelism but its sensitivity to chemical deterioration.

2. List of Modules
Introduction to D.N.A.
Adleman's Experiment
Applications of D.N.A. based systems
DNA based computers Vs. Conventional
Computers
Conclusion

3. Introduction to
D.N.A.

4. What is DNA ?
• DNA is an abbreviation for Deoxyribonucleic
Acid.
• DNA contains the genetic blueprint of living
creatures.
• DNA contains the instructions for assembling
cells in the body.
• Every cell in the body has a complete set of
DNA.
• DNA is unique for each individual.

5. Structure of DNA
• Sides:
• Sugar-Phosphate backbone
• Ladders
• Four complimentary base pairs
• Adenine and Thymine
• Guanine and Cytosine
• The base pairs contain weak hydrogen bonds
which hold the strands together.

6. Salient features of DNA
• DNA Replication
• Replication is the method by which any molecule
can form an exact replica of itself and the DNA gets
embedded in both these daughter molecules.
• DNA Extraction
• In this method, it is possible to separate and bring
together different strands of DNA that are of the
same type.
• DNA Annealing
• This is the method by which two DNA strands can be
brought together and then paired together or
melted to form one single entity.

7. Uniqueness of D.N.A.
• Extremely dense information storage.
• 1 gm DNA = 1 X 1014 bits
• Parallelism
• 3 X 1014 molecules at a time
• Energy efficiency
• 1 Joule = 2 X 1019 operations

8. Adleman’s Experiment

9. Adleman’s approach
I believe things like DNA computing
will eventually lead the way to a
molecular revolution which ultimately
will have a very dramatic effect on
the world
-L. Adleman

10. Hamiltonian Directed Path
Problem (HDPP)
• Problem Statement
• Consider a salesman who has to travel to a number
of cities on a daily basis. Now the problem is to find
for him the fastest route, without taking him
through the same city twice.
Delhi
(Source)
Mumbai
Kolkata
Bangalore
Kochi
(Destination)

11. Solution
• The solution can be found out by using the
replication property of DNA.
• Several options can be checked at once as DNA
performs parallel processing.
• So far this method has been successful up to
15 cities.
• With advancements almost daily the no. of
cities are sure to rise up.

12. Adleman’s Algorithm
• Generate all possible routes.
• Select itineraries that start with proper city
and end with the final city.
• Gel Electrophoresis.
• Select itineraries which contain each city only
once.

13. 1.Generate all possible routes
• For this purpose, we encode all the cities:
CITIES CODES
Delhi GCTACG
Mumbai CTAGTA
Kolkata TCGTAC
Bangalore CTACGG
Kochi ATGCCG

14. 1.Generating all possible routes
(Continued)
• Now we encode the itineraries by connecting the
city sequences for which routes exist.
• Example
• Bangalore=CTACGG
• Kochi=ATGCCG
• Let S1 be the path from Bangalore to Kochi.
• S1 = CGGATG
• Now we compute, S1 = GCCTAC
• Now the for Bangalore to Kochi = GCCTAC
• Similarly, we will find the codes for all the paths.

15. 2.Select desired itineraries
• The next step is to select the itineraries that
start and end with the correct route. The
strategy is to selectively cope and amplify only
that DNA which starts with Delhi and end with
Kochi.
Delhi
(Source)
Kochi
(Destination)

16. 3.Gel Electrophoresis
• Sort the DNA by length and select the DNA
whose length equals to 5 cities.
• Generally, the DNA is a negatively charged
molecule, having a constant charge density.
The GEL slows down the passing of DNA
depending on the lengths therefore, producing
bands. “The technique used is GEL
Electrophoresis. It is used to differentiate
between DNA molecules having different
lengths”.

17. 3.Gel Electrophoresis Diagram

18. 4.SolutionPaths encoding
Cities Path
Symbol
Code Compliments
Delhi to Mumbai S1 TGCGAT ACGCTA
Mumbai to Kolkata S2 CATAGC GTATCG
Kolkata to Bangalore S3 ATGGCC TACCGG
Bangalore to Kochi S4 GCCTAG CGGATC

19. 4.Select itineraries which
contain each city only once.
Delhi
(Source)
Mumbai Kolkata
BangaloreKochi
(Destination)
S1 S2
S3
S4

20. Applications on DNA
based computing

21. Applications of DNA based
computing
• Solving NP-complete and hard computational
problems
• Storage and Associative memory
• DNA 2 DNA Problems
• DNA Sequencing
• DNA Fingerprinting
• DNA mutation detection

22. DNA based computers Vs.
Conventional Computers

23. DNA based computers Vs.
Conventional Computers
DNA based computers Conventional Computers
 Can do billions of operations
simultaneously.
 Can do substantially fewer
operations simultaneously.
 Can provide huge memory in small
space.
 Smaller memory.
 Setting up a problem may require
considerable preparations.
 Setting up only requires keyboard
input.
 DNA is sensitive to chemical
deterioration.
 Electronic data is vulnerable but
can be backed up easily.

24. Conclusion

25. Conclusion
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