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Paushali sen 
MCA 3nd yr 5th sem
Overview 
 Introduction to DNA 
 What is DNA computing 
 Adleman’s Hamiltonian path problem. 
 Cutting Edge Technologi...
What is DNA? 
• DNA stands for Deoxyribonucleic Acid 
• DNA represents the genetic blueprint of living 
creatures 
• DNA c...
Double Helix 
• “Sides” 
Sugar-phosphate backbones 
• “ladders” 
complementary base pairs 
Adenine & Thymine 
Guanine & Cy...
Uniqueness of DNA 
Why is DNA a Unique Computational Element??? 
• Extremely dense information storage. 
• Enormous parall...
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 ...
Storeing info inside DNA 
 The following technique use for 
copying,sorting,concating and spliting info into DNA 
module ...
Steps of DNA computing 
 Encodind schame 
 Ligation and hybridization 
 Polymerase Chain Reaction (PCR) 
 Affinity Sep...
Encoding schame 
 Encode each object of interest into DNA sequence 
 A correct design is necessary 
 Incorrect design c...
Ligation and hybridization 
 The sequence when DNA drop in a test tube using a 
micro pipattor 
 DNA sequences recombine...
Picture of dropers and 
hybridization 
 Droppers 
 hybridization
Polymerase chain reaction 
 . Initialization: a mix solution of template, primer, dNTP and enzyme 
isheated to 94 − 98◦C ...
Affinity saparation 
 Varify each of data include acertain sequinence or not 
 process a double stranded DNA is incubate...
pictures
Gel electrophoresis 
 charged molecules to move in an electric field 
 Basically, DNA molecules carry negative charge.Th...
How enormous is the 
parallelism? 
• A test tube of DNA can contain trillions of 
strands. Each operation on a test tube o...
How extraordinary is the 
energy efficiency? 
• Adleman figured his computer was running 
2 x 1019 operations per joule.
Can DNA compute? 
 DNA itself does not carry out any computation. It 
rather acts as a massive memory. 
 BUT, the way co...
DNA COMPUTING 
 A computer that uses DNA (deoxyribonucleic 
acids) to store information and perform complex 
calculations...
Adleman’s Experiment 
• Hamilton Path Problem 
(also known as the travelling salesperson problem) 
Perth 
Darwin 
Brisbane...
Adleman’s Experiment 
• Solution by inspection is: 
Darwin  Brisbane  Sydney  Melbourne  Perth  
Alice Spring 
• BUT,...
Adleman’s Experiment 
1. Encode each city with complementary base - 
vertex molecules 
Sydney - TTAAGG 
Perth - AAAGGG 
Me...
Adleman’s Experiment (Cont’d) 
2. Encode all possible paths using the 
complementary base – edge molecules 
Sydney  Melbo...
Adleman’s Experiment (Cont’d) 
3. Merge vertex molecules and edge molecules. 
All complementary base will adhere to each o...
Adleman’s Experiment (Cont’d) 
• The solution is a double helix molecule: 
Darwin Brisbane Sydney Melbourne Perth Alice Sp...
Operations (Cont’d) 
• Merging 
mixing two test tubes with many DNA molecules 
• Amplification 
DNA replication to make ma...
THE FUTURE! 
Algorithm used by Adleman for the traveling salesman 
problem was simple. As technology becomes more 
refine...
DNA computers are unlikely to feature word 
processing, emailing and solitaire programs. 
Instead, their powerful comput...
DNA Chip
Chemical IC
The Smallest Computer 
• The smallest programmable DNA computer was 
developed at Weizmann Institute in Israel by Prof. 
E...
Pros and Cons 
+ Massively parallel processor 
DNA computers are very good to solve Non-deterministic 
Polynomial problems...
Pros and Cons (Cont’d) 
- Requires constant supply of proteins and 
enzymes which are expensive 
- Errors occur frequently...
DNA Vs Electronic computers 
 At Present, NOT competitive with the state-of-the-art 
algorithms on electronic computers 
...
Conclusion 
• Many issues to be overcome to produce a 
useful DNA computer. 
• It will not replace the current computers 
...
Thank you
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Power point presentation of saminer topic DNA based computing

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Power point presentation of saminer topic DNA based computing

  1. 1. Paushali sen MCA 3nd yr 5th sem
  2. 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. 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. 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. 5. Uniqueness of DNA Why is DNA a Unique Computational Element??? • Extremely dense information storage. • Enormous parallelism. • Extraordinary energy efficiency.
  6. 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. 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. 8. Steps of DNA computing  Encodind schame  Ligation and hybridization  Polymerase Chain Reaction (PCR)  Affinity Separation  Gel Electrophoresis
  9. 9. Encoding schame  Encode each object of interest into DNA sequence  A correct design is necessary  Incorrect design can make the system incorrect
  10. 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
  11. 11. Picture of dropers and hybridization  Droppers  hybridization
  12. 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. 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
  14. 14. pictures
  15. 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. 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. 17. How extraordinary is the energy efficiency? • Adleman figured his computer was running 2 x 1019 operations per joule.
  18. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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.
  29. 29. DNA Chip
  30. 30. Chemical IC
  31. 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. 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. 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. 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. 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.
  36. 36. Thank you

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