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Presented by
Ch Naveen Kumar

 Introduction
 History
 Representation of DNA computing
 Representation of DNA chip
 DNA v/s Silicon computer
 Benefits of DNA computing
 Applications
 Advantages
 Disadvantages
 Limitations
 Future
 Conclusion
Conents
 DNA means “Deoxyribonucleic Acid”.
 DNA computing is a branch of computing.
 “Computation using DNA ”but not” computation on
DNA”.
 A Nano computer that uses DNA to store information
and perform complex calculations.
INTRODUCTION

In 1994 University of Southern California computer
scientist Leonard Adlemen suggested that DNA
could be used to solve complex mathematical
problems.
Adelman found away to harness the power of DNA
to solve the Hamilton path problem whose solution
required finding a path from start to ending
through all the points to visit only once(it is also
known as travelling salesman problem).
HISTORY

 In DNA computing information is represented using
four characters genetic alphabet .
 ( A [adenine], G [guanine], C [cytosine] and T
[thymine] ) rather than binary alphabet (1 or 0) used
by traditional computers.
Representation of DNA
computing


Representation of DNA
chip

 Traditional silicon based computer have a limited
speed and beyond a point cannot be miniaturize.
 Information storage capacity of DNA molecule is
much higher than silicon chips.
 1gm of DNA can store huge amount of data such has
1*1014mb of data’, to listen to the same amount of
data stored in a cd will require 1,63,000 centuries.
 It is cheaper than silicon.
DNA v/s Silicon computer

To solve complex problems is that different
possible solutions are created all at once this is
known as parallel processing.
Here humans and most electronics computers
must attempt to solve problem one process at a
time(linear processing).
DNA molecular can fit into an area no large than
one cubic cm . with this DNA a computation
could hold 10TB of data and perform 10trillion
calculation at a time.
Benefits of DNA

DNA chips
Genetic programming
Pharmaceutical applications
Cracking of coded messages
DNA finger printing
Applications of DNA
computing

 This are light weight computers.
 Power or electricity required for DNA computation
are very less , power is needed only to present the
DNA from denaturation.
 The main advantage of DNA computing is it can
solve the hardest problem very quickly were
compared to traditional silicon computer.
Advantages of DNA
computing

 It takes much time to solve a simple problem.
 It takes longer time to sort out the answer to a
problem that it took’s to solve the same problem.
Disadvantages of DNA
computing

 It involves a relatively large amount of error.
 Requires human assistance.
 Time consuming laboratory procedures.
 No universal method of data representation.
Limitations / current
problems

 Algorithm used by Adleman for the traveling
salesman problem was simple . As technology
becomes refined ,more efficient algorithms may be
discovered.
 In future advances DNA computers are more
admission.
The future

 The field of DNA computation is truly exciting for
the revolution implies will occur with in next few
years.
 Intel scientist say it happens about in year 2018.
 It shows enormous potential, especially for medical
purpose as well as data processing applications.
Conclusion

Thanks you

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Dna computing

  • 2.   Introduction  History  Representation of DNA computing  Representation of DNA chip  DNA v/s Silicon computer  Benefits of DNA computing  Applications  Advantages  Disadvantages  Limitations  Future  Conclusion Conents
  • 3.  DNA means “Deoxyribonucleic Acid”.  DNA computing is a branch of computing.  “Computation using DNA ”but not” computation on DNA”.  A Nano computer that uses DNA to store information and perform complex calculations. INTRODUCTION
  • 4.  In 1994 University of Southern California computer scientist Leonard Adlemen suggested that DNA could be used to solve complex mathematical problems. Adelman found away to harness the power of DNA to solve the Hamilton path problem whose solution required finding a path from start to ending through all the points to visit only once(it is also known as travelling salesman problem). HISTORY
  • 5.   In DNA computing information is represented using four characters genetic alphabet .  ( A [adenine], G [guanine], C [cytosine] and T [thymine] ) rather than binary alphabet (1 or 0) used by traditional computers. Representation of DNA computing
  • 6.
  • 8.   Traditional silicon based computer have a limited speed and beyond a point cannot be miniaturize.  Information storage capacity of DNA molecule is much higher than silicon chips.  1gm of DNA can store huge amount of data such has 1*1014mb of data’, to listen to the same amount of data stored in a cd will require 1,63,000 centuries.  It is cheaper than silicon. DNA v/s Silicon computer
  • 9.  To solve complex problems is that different possible solutions are created all at once this is known as parallel processing. Here humans and most electronics computers must attempt to solve problem one process at a time(linear processing). DNA molecular can fit into an area no large than one cubic cm . with this DNA a computation could hold 10TB of data and perform 10trillion calculation at a time. Benefits of DNA
  • 10.  DNA chips Genetic programming Pharmaceutical applications Cracking of coded messages DNA finger printing Applications of DNA computing
  • 11.   This are light weight computers.  Power or electricity required for DNA computation are very less , power is needed only to present the DNA from denaturation.  The main advantage of DNA computing is it can solve the hardest problem very quickly were compared to traditional silicon computer. Advantages of DNA computing
  • 12.   It takes much time to solve a simple problem.  It takes longer time to sort out the answer to a problem that it took’s to solve the same problem. Disadvantages of DNA computing
  • 13.   It involves a relatively large amount of error.  Requires human assistance.  Time consuming laboratory procedures.  No universal method of data representation. Limitations / current problems
  • 14.   Algorithm used by Adleman for the traveling salesman problem was simple . As technology becomes refined ,more efficient algorithms may be discovered.  In future advances DNA computers are more admission. The future
  • 15.   The field of DNA computation is truly exciting for the revolution implies will occur with in next few years.  Intel scientist say it happens about in year 2018.  It shows enormous potential, especially for medical purpose as well as data processing applications. Conclusion