DNA Computing Presentation, Slides of Computer Science

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PRESENTATION

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DNA COMPUTING Presented By a.Aparna

contents ➢ What is DNA? ➢ Structure of DNA ➢ What is a DNA computer? ➢ DNA computing ➢ Hamiltonian path problem ➢ Advantages ➢ Disadvantages ➢ Applications ➢ Conclusion

Structure of dna

➢DNA is made up of molecules called nucleotides. ➢Each nucleotide contains a phosphate group, a sugar group and a nitrogen base. ➢The four types of nitrogen bases are adenine(A) thymine(T) guanine(G) cytosine(C) ➢The order of nitrogen bases determines genetic code.

➢ DNA computing is a branch of computing which uses DNA, biochemistry and molecular biology hardware, instead of traditional silicon based computer technologies. ➢ Leonard Adleman presented the first prototype of DNA computer. ➢ DNA itself does not carry out any computation rather acts as a massive memory.

DNA Computing

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 1 x 10 14 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.

Steps To Follow:-

➢ Generate all possible routes. ➢ Select path that start with the proper city and end with final city. ➢ Select path with the correct no. of cities. ➢ Select path that contain each city only once.

➢ Encode city names in short DNA sequences. Encode path by connecting the city sequence for which routes exist. Miami C T A C G G Miami to NewYork G C C T A C NewYork A T G C C G City Encoding Route Encoding Miami C T A C G G NewYork A T G C C G G C C T A C Miami to NewYork Hybridized DNA Los Angeles GCTACG Chicago CTAGTA Dallas TCGTAC Miami CTACGG New York ATGCCG

disadvantages

➢ Techniques that reduce error rates have to be developed. ➢ Requirement of DNA increases as complexity of the problem increases. ➢ Handling easily breakable DNA molecules during manufacture of biochips is difficult. ➢ If DNA computers are forced to operate serially, their performance becomes very poor.

applications

➢ DNA chips ➢ DNA fingerprinting ➢ Medical application ➢ Cracking of coded messages ➢ Solving NP-hard problems ➢ Turing machine ➢ Boolean circuits

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