1. DNA Computing Guided by: Ms. Leena Patel Computer Engineering Prepared by: Devharsh Trivedi 09 012 01 07 059

2.  Evolution  What is DNA?  DNA Computing  Travelling salesman  DNA v/s Silicon  Advantages  Disadvantages  Reviews  Conclusion  References

3. Evolution 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. - Leonard Max Adleman, 1995. Began in 1994 when Dr. Leonard Adleman wrote the paper “Molecular computation of solutions to combinatorial problems”. Leonard Adleman proposed that the makeup of DNA and its multitude of possible combining nucleotides could have application in computational research techniques.

4. What is DNA? D : Deoxy Ribo N : Nucleic A : Acid Source code to life. Instructions for building and regulating cells. Data store for genetic inheritance. DNA carries the genetic information of a cell.

5. Definition: DNA computers are the computers which are using enzymes (Cellular machinery) as a program that processes on DNA molecules. Think of enzymes as hardware, DNA as software.

7. The field of DNA computing is concerned with the possibility of performing computations using biological molecules. DNA computer is a computer that “computes” using enzymes that react with DNA strands, causing reactions. These reactions act as a kind of simultaneous computing or parallel processing. A DNA-based finite automaton computes via repeated cycles of self assembly and processing.

9. Travelling Salesman Problem # Algorithm:- 1.Generate all possible routes 2.Select routes that start with the initial city and end with the destination city 3.Select itineraries with the correct number of cities 4.Select itineraries that contain each city once

11. DNA v/s Silicon  Transistor-based computers typically handle operations in a sequential manner.  DNA computers are non-von Neumann machines.  Many copies of the replication enzymes are allowed to work on DNA in parallel.  With each additional strand, the data rate increases by 1000 bits/sec.  The number of DNA strands increases exponentially (2^n after n iterations).

13. Advantages i. Parallel Computing ii. Incredibly light weight iii. Low power Dissipation iv. Solves Complex Problems quickly v. Gigantic Memory Capacity vi. Clean, Cheap and Available

14. Disadvantages i. Occasionally slower ii. Hydrolysis iii. Information Untransmittable iv. Reliability Problems v. Annealing (or hybridization) Errors vi. High cost is time

15. Reviews Limitations: I. DNA computing involves a relatively large amount of error II. Requires human assistance! III. Time consuming laboratory procedures. IV. No universal method of data representation. Applications: I. DNA chips II. Genetic programming III. Pharmaceutical applications IV. Cracking of coded messages

16. Conclusion The paradigm of DNA computing has lead to a very important theoretical research. However DNA computers won’t flourish soon in our daily environment due to the technologic issues.

17. References:  http://computer.howstuffworks.com/dna- computer.htm http://computer.howstuffworks.com/dna- computer.htm  http://webopedia.com/TERM/D/DNA_co mputer.html http://webopedia.com/TERM/D/DNA_co mputer.html  http://britannica.com/EBchecked/topic/94 1575/DNA-computing http://britannica.com/EBchecked/topic/94 1575/DNA-computing  http://dna-computing.org http://dna-computing.org  http://dna-sequencing-service.com/dna- sequencing/dna-computing http://dna-sequencing-service.com/dna- sequencing/dna-computing