The document provides an overview of DNA computing, including its history, basics, applications, advantages, disadvantages, limitations, and future potential. DNA computing utilizes the massive parallelism of DNA to solve complex problems. Some key advantages are that DNA computing can perform millions of operations simultaneously and efficiently handle large amounts of data. However, limitations include relatively high error rates and the need for time-consuming laboratory procedures. While not replacing traditional computers, DNA computing may be useful for applications such as genetic programming, drug discovery, and encryption in the future.

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www.studymafia.org
Seminar
On
DNA Computing

2. Content
 Introduction
 Need for DNA Computing
 Limitations / Current Problems
 Applications of DNA Computing
 Advantages of DNA Computing
 Disadvantages of DNA Computing
 Why don’t we see DNA computers everywhere?
 The Future!
 Conclusion
 Reference

3. Introduction
 What is DNA computing ?
 Around 1950 first idea (precursor Feynman)
 First important experiment 1994: Leonard
Adleman
 Molecular level (just greater than 10-9 meter)
 Massive parallelism.
 In a liter of water, with only 5 grams of DNA we
get around 1021 bases !
 Each DNA strand represents a processor !

4. History
 This field was initially developed by Leonard
Adleman of the University of Southern California, in
1994.
 Adleman demonstrated a proof-of-concept use of
DNA as a form of computation which solved the
seven-point Hamiltonian path problem.
 Since the initial Adleman experiments, advances
have been made and various Turing machines have
been proven to be constructible

5. Basics And Origin of DNA
Computing
 DNA computing is utilizing the property of DNA for
massively parallel computation.
 With an appropriate setup and enough DNA, one can
potentially solve huge problems by parallel search.
 Utilizing DNA for this type of computation can be much faster
than utilizing a conventional computer
 Leonard Adleman proposed that the makeup of DNA and its
multitude of possible combining nucleotides could have
application in computational research techniques.

6. Need for DNA Computing
 Conventional or traditional silicon based computers have a
limited speed and beyond a point cannot be miniaturize.
 Information storage capacity of DNA molecule is much higher
than the silicon chips. One cubic nanometre of DNA is
sufficient to store 1bit information
 Operations on DNA computing are parallel, test tube of DNA
may contain around trillions of strands. Each operation is
carried out in all the strands present in the test tube parallel.
 1 gram of DNA can store a huge amount of data such as 1 �-
1014 MB of data; to listen to the same amount of data stored
in a CD will require 163,000 centuries.

7. Limitations / Current
Problems
 It involves a relatively large amount of error.
 Requires human assistance.
 Time consuming laboratory procedures.
 No universal method of data representation .

8. Applications of DNA Computing
 DNA chips
 Genetic programming
 Pharmaceutical applications
 Cracking of coded messages
 DNA fingerprinting

9. Advantages of DNA
Computing
 Perform millions of operations simultaneously
 Generate a complete set of potential solutions
 Conduct large parallel searches
 Efficiently handle massive amounts of working memory
 Cheap, clean, readily available materials
 Amazing ability to store information

10. Disadvantages of DNA
Computing
 Generating solution sets, even for some relatively
simple problems, may require impractically large
amounts of memory (lots and lots of DNA strands are
required)
 DNA computers could not (at this point) replace
traditional computers.
 They are not programmable and the average dunce
can not sit down at a familiar keyboard and get to
work.

11. Why don’t we see DNA
computers everywhere?
 DNA computing has wonderful possibilities:
 Reducing the time of computations* (parallelism)
 Dynamic programming !
 However one important issue is to find “the killer
application”.
 Great hurdles to overcome…

12. 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.
 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.

13. 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.

14. Reference
 www.google.com
 www.wikipedia.com
 www.studymafia.org

15. Thanks

16. Queries?