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Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
Bio_Computing
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Bio_Computing

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My First paper

My First paper

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  • 1. DNA COMPUTERS By V.Meera C.Meenakshi (St.Peter’s Engineering college)
  • 2. CONTENTS
    • Why DNA Computers
    • DNA-In a nut shell
    • DNA structure
    •  Advantages
    • Features of DNA computers
    •  Memory
    •  Parallelism
    •  Power Generation
    •  Operations in DNA
    • Silicon Computers Vs DNA Computers <Similarities and Difference>
    • Applications
    • Conclusions
  • 3. Why DNA Computers?
    • Moore’s Law states that silicon microprocessors double in complexity roughly every two years.
    • To overcome the limitations of Current Computing Technology. BIO-Chips made up of DNA is used as a substitute for sillicon chips.
  • 4. DNA-In a Nut Shell
    • DNA -D eoxyribo N ucleic A cid
    • All organisms on this planet are made of the same type of genetic blueprint.
    • Within the cells of any organism is a substance called DNA which is a double-stranded helix of nucleotides.
    • DNA carries the genetic information of a cell.<Memory in DNA computers>
  • 5. DNA Structure
    • Each strand is based on 4 bases:
    • >Adenine (A)
    • >Thymine (T)
    • >Cytosine (C)
    • >Guanine (G)
  • 6. DNA Structure…
    • Due to the hybridization reaction, A is complementary with T and C is complementary with G.
  • 7. Features Of DNA Computers
    • PARALLELISM
    • The process of carrying out different operations in different strands at the same time.
    • Replication
    • Reason for Enormous parallelism of DNA computers .
  • 8. Replication
  • 9. Parallelism……
    • If forced to behave sequentially, DNA loses its appeal .
    • Eg:
    • Will doubling the clock speed or doubling
    • your RAM give you better performance?
  • 10. Parallelism……
    • Proof:
    • Read and write rate of DNA:
    • <DNA of Bacteria is taken as sample>
    • Case 1: If single copy of the replication enzymes to work in sequential manner.
    • Case 2: If many copies of the replication
    • enzymes to work on DNA in parallel.
  • 11. Memory
    • The 1 gram of DNA can hold about 1x1014 MB of data.
    • 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
  • 12. No More Viruses
  • 13. Virus Resistance
    • In DNA Computers
    • > Here viruses effects the base pairs of the DNA .
    • > There are various error correction mechanisms that autocorrects the base pairs.
    • >PCR detects a erroneous DNA strand.
    • >Err in one DNA does not affect the whole system.
    • So Adieu Anti-Virus!!!
  • 14. Power Generation
    • A DNA polymer molecule stores significant amount of energy relative to the same polymer broke into little pieces - its monomers. The DNA computer uses this energy to drive a useful process, namely computation .
  • 15. Operations In DNA Computers…
    • Logical operations in DNA computers:
    • DNA logic gates pick up various fragments
    • single of a genome as input before creating a
    • output from the fragments
  • 16. Logical Operations in DNA Computers
    • Typical logic gate operations can be explained as below :
    • OR:
    • - pouring together DNA solutions containing
    • specific sequences .
    • AND:
    • - Separating DNA strands according to their
    • sequences
  • 17. Logical Operations in DNA Computers..
    • EX-OR:
    • - If the DNA at the input is a complementary strand they combine to give a 1.
  • 18. Operations In DNA Computers
    • Steps to perform the logic operations:
    • STEP 1:
    • Chemical structure of the DNA is found.
  • 19. Operations In DNA Computers…
    • STEP 2:
    • The DNA strands are separated and placed in a solid substrate or in a liquid. This is the reference strand .
  • 20. Operations In DNA Computers…
    • STEP 3:
    • Another DNA strand to which the operation is to be done is introduced.
  • 21. Operations In DNA Computers…
    • STEP 4:
    • After the hybridization a bond is formed between two strands which yields the result.
  • 22. The truth table for DNA logic gates
    • The truth table in a DNA computers uses a three-level scheme.
    • An operation is represented in terms of DNA hybridisation.
    • For each binary operation the two bit strings are represented with two different DNA single strands.
    • The first string is called the “input” and the second is the “operand”.
  • 23. Truth table for DNA Computers….
    • Each bit is represented with a dinucleotide unit, and a bit string with a sequence of dinucleotides
    • Bases used in encoding are
    • >A-Adenine
    • >T-Thymine
    • >U-Uracil
    • >P-2,6-diaminopurine
  • 24. Truth table encoding using “dinucleotide” bits .
  • 25. Sample operation
    • Eg: 1001 NAND 0101
    • Input string:1001
    • Operand :0101
  • 26. Conventional Computers Vs DNA Computers
  • 27. Applications
    • DNA fingerprinting.
    • Airline and communication routing <NP –Problem>
    • DNA chips.
    • Genetic programming.
    • Pharmaceutical applications.
    • Cracking of coded messages
  • 28. NP Problem made easy
    • E.g.:
    • Hamiltonian Problem
    • Statement:
    • Given a graph with directed edges, find a Hamiltonian Path, i.e. a path which starts at one node, finishes at another, and goes through all other nodes exactly once.
  • 29. NP Problem made easy…..
    • Edges represent non-stop flights
    • Determine whether there is a Hamiltonian Path starting in Atlanta,ending in Detroit
  • 30. Steps to solve the problem
    • Step 1: Encode this graph in a DNA.
  • 31. Steps to solve the problem..
    • Step 2: Vertices are assigned a random DNA sequence
    • o Atlanta: ACTT GCAG
    • o Boston: TCGG ACTG
  • 32. Steps to solve the problem..
    • Step 3:
    • Edges (flights) are formed by concatenating
    • the 2nd half of the originating city and the 1st
    • half of the destination city
      • >Atlanta-Boston: GCAG TCGG
    • Step 4:
    • Use Polymerase Chain Reaction (PCR) to
    • replicate DNA with the correct start and end
    • city.
  • 33. Steps to solve the problem..
    • Step 5:
    • Put one primer on Atlanta and one primer on
    • Detroit.
    • Step 6:
    • The right answer is replicated exponentially,
    • while the wrong paths are replicated linearly or
    • not at all.
  • 34. Steps to solve the problem..
    • Step 7:
    • Use gel electrophoresis to identify the molecules with the right length.
    • Step 8:
    • Finally, use affinity separation procedure to
    • weed out paths without all the cities.
  • 35. Steps to solve the problem..
    • Step 9:
    • Probe molecules attached on iron balls attract
    • the correct strands; the rest is poured out.
    • Step 10:
    • If any DNA is left in the tube, it is the Hamiltonian Path.
  • 36. Applications
    • DNA fingerprinting.
    • Airline and communication routing <NP –Problem>
    • DNA chips.
    • Genetic programming.
    • Pharmaceutical applications.
    • Cracking of coded messages
  • 37. Conclusions
    • DNA computers showing enormous
    • potential, especially for medical as well
    • as data processing applications.
    • Still lots of work resources required to
    • develop it into a fully fledged product.
  • 38. QUERIES???

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