DNA Based Computing
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DNA computing is a novel approach that uses DNA, RNA, and biochemical reactions to solve computational problems. The document outlines Adleman's experiment using DNA to solve the Hamiltonian path problem. It then discusses applications of DNA computing such as solving NP-complete problems, data storage, DNA sequencing, and mutation detection. Finally, it compares DNA computers to conventional computers, noting DNA's ability to perform massive parallelism but its sensitivity to chemical deterioration.
DNA Based Computing
- 2. List of Modules Introduction to D.N.A. Adleman's Experiment Applications of D.N.A. based systems DNA based computers Vs. Conventional Computers Conclusion
- 4. What is DNA ? • DNA is an abbreviation for Deoxyribonucleic Acid. • DNA contains the genetic blueprint of living creatures. • DNA contains the instructions for assembling cells in the body. • Every cell in the body has a complete set of DNA. • DNA is unique for each individual.
- 5. Structure of DNA • Sides: • Sugar-Phosphate backbone • Ladders • Four complimentary base pairs • Adenine and Thymine • Guanine and Cytosine • The base pairs contain weak hydrogen bonds which hold the strands together.
- 6. Salient features of DNA • DNA Replication • Replication is the method by which any molecule can form an exact replica of itself and the DNA gets embedded in both these daughter molecules. • DNA Extraction • In this method, it is possible to separate and bring together different strands of DNA that are of the same type. • DNA Annealing • This is the method by which two DNA strands can be brought together and then paired together or melted to form one single entity.
- 7. Uniqueness of D.N.A. • Extremely dense information storage. • 1 gm DNA = 1 X 1014 bits • Parallelism • 3 X 1014 molecules at a time • Energy efficiency • 1 Joule = 2 X 1019 operations
- 9. Adleman’s approach 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 -L. Adleman
- 10. Hamiltonian Directed Path Problem (HDPP) • Problem Statement • Consider a salesman who has to travel to a number of cities on a daily basis. Now the problem is to find for him the fastest route, without taking him through the same city twice. Delhi (Source) Mumbai Kolkata Bangalore Kochi (Destination)
- 11. Solution • The solution can be found out by using the replication property of DNA. • Several options can be checked at once as DNA performs parallel processing. • So far this method has been successful up to 15 cities. • With advancements almost daily the no. of cities are sure to rise up.
- 12. Adleman’s Algorithm • Generate all possible routes. • Select itineraries that start with proper city and end with the final city. • Gel Electrophoresis. • Select itineraries which contain each city only once.
- 13. 1.Generate all possible routes • For this purpose, we encode all the cities: CITIES CODES Delhi GCTACG Mumbai CTAGTA Kolkata TCGTAC Bangalore CTACGG Kochi ATGCCG
- 14. 1.Generating all possible routes (Continued) • Now we encode the itineraries by connecting the city sequences for which routes exist. • Example • Bangalore=CTACGG • Kochi=ATGCCG • Let S1 be the path from Bangalore to Kochi. • S1 = CGGATG • Now we compute, S1 = GCCTAC • Now the for Bangalore to Kochi = GCCTAC • Similarly, we will find the codes for all the paths.
- 15. 2.Select desired itineraries • The next step is to select the itineraries that start and end with the correct route. The strategy is to selectively cope and amplify only that DNA which starts with Delhi and end with Kochi. Delhi (Source) Kochi (Destination)
- 16. 3.Gel Electrophoresis • Sort the DNA by length and select the DNA whose length equals to 5 cities. • Generally, the DNA is a negatively charged molecule, having a constant charge density. The GEL slows down the passing of DNA depending on the lengths therefore, producing bands. “The technique used is GEL Electrophoresis. It is used to differentiate between DNA molecules having different lengths”.
- 18. 4.SolutionPaths encoding Cities Path Symbol Code Compliments Delhi to Mumbai S1 TGCGAT ACGCTA Mumbai to Kolkata S2 CATAGC GTATCG Kolkata to Bangalore S3 ATGGCC TACCGG Bangalore to Kochi S4 GCCTAG CGGATC
- 19. 4.Select itineraries which contain each city only once. Delhi (Source) Mumbai Kolkata BangaloreKochi (Destination) S1 S2 S3 S4
- 20. Applications on DNA based computing
- 21. Applications of DNA based computing • Solving NP-complete and hard computational problems • Storage and Associative memory • DNA 2 DNA Problems • DNA Sequencing • DNA Fingerprinting • DNA mutation detection
- 22. DNA based computers Vs. Conventional Computers
- 23. DNA based computers Vs. Conventional Computers DNA based computers Conventional Computers Can do billions of operations simultaneously. Can do substantially fewer operations simultaneously. Can provide huge memory in small space. Smaller memory. Setting up a problem may require considerable preparations. Setting up only requires keyboard input. DNA is sensitive to chemical deterioration. Electronic data is vulnerable but can be backed up easily.
- 24. Conclusion
- 25. Conclusion • •