Dna Ppt Final

Sandeep M 1bj05cs032

Contents 

Traditional Computers  Introduction to DNA  Structure of DNA  DNA Computers  Advantages & Disadvantages  Develoments in DNA Computing  References

Traditional Computation 

Traditional computers started with vacuum tubes, mechanical switches.  Now we have IC’s and processors with VLSI, ULSI technologies.  These computers are examples of Von Neumann architecture.

Traditional Computation (continued) 

Silicon is the life for today's computers.  Moore’s Law states that silicon microprocessors double in complexity roughly every two years.  One day this will no longer hold true when miniaturisation limits are reached.  Require a successor to silicon.

What is DNA ? 

Deoxyribonucleic acid (DNA) is a nucleic acid that contains the genetic instructions used in the development and functioning of all known living organisms.  DNA is nothing but blueprint or a code, since it contains the instructions needed to construct other components of cells, such as proteins and RNA molecules.

Structure of DNA

Structure of DNA (continued) 

Chemically, DNA consists of two long polymers of simple units called nucleotides, with backbones made of sugars and phosphate groups joined by ester bonds.  These two strands run in opposite directions to each other and are therefore anti-parallel.  There are 4 nucleotides in DNA A – Adenine T –Thymine C – Cytosine G – Guanine

DNA Computing 

DNA computing is a form of computing which uses DNA, biochemistry and molec ular biology, instead of the traditional silicon-based computer technologies.  This field was initially developed by Leonard Adleman of the University of Southern California, in 1994.

DNA Computing(continued) 

Adleman demonstrated a proof-ofconcept use of DNA as a form of computation which solved the sevenpoint Hamiltonian path problem.  DNA computers are faster and smaller than any other computer built so far. But DNA computing does not provide any new capabilities from the standpoint of computability theory .

Computation Algorithm 



STEP1:Encode the city names in short DNA sequences . Encode the Itineraries by connecting the city sequences for which the routes exist . CITY

DNA SEQUENCE

MUMBAI

GCTACG

DELHI

CTAGTA

BANGALORE

TCGTAC

CHENNAI

CTACGG

KOLKATA

ATGCCG

The DNA molecules are generated by a machine called DNA synthesizer

•Polymerase chain reaction is used to produce many copies of the DNA •PCR is iterative and uses an enzyme called polymerase •Polymerase copies a section of single stranded DNA starting at the position of the primer, which is DNA complimentary to one end of the Interested section.

Step 2: Sort the DNA by length and select the DNA whose length Corresponds to 5 cities.

• •

Gel electrophoresis force the DNA through a gel matrix by using an electric field. DNA forces its way through the gel which slows down the DNA at different rates.

STEP 3:Successively filter the DNA molecules by city, one city at a Time. •Finally, use affinity separation procedure to weed out paths without all the cities •Iterative procedure (for each vertex/city) •Probe molecules attached on iron balls attract the correct strands; the rest is poured out •If any DNA is left in the tube, it is the Hamiltonian Path.

Advantages The power of DNA in view of computation capability:  vast parallelism: 10 trillion ligation reaction could be done simultaneously in a marblesized space.  exceptional energy efficiency: 2×1019 operations/J, theoretical bound 3×1019 operations/J, existing computer: 109 operations/J.  extraordinary information density: 1gram = 4×1021 bits = 1 trillion CDs.

Disadvantages 

DNA computing involves a relatively large amount of error.  Requires human assistance!  Time consuming laboratory procedures.  No universal method of data representation. 

DNA has a half-life. Solutions could dissolve away before the end

result is found

DNA V/s Conventional Computer

Developments in DNA computation  Began in 1994 when Dr. Leonard Adleman wrote the paper “Molecular computation of solutions to combinatorial problems” & succeeded in using it.  First practical DNA computer unveiled in 2002 by Olympus Optical Co., Ltd . Used in gene analysis. DNA computer for gene analysis (development prototype). High-speed fullyautomated process from sample injection to reaction enables quantitative gene expression profiling.

Developments in DNA computation(continued) Self-powered DNA computer unveiled in 2003. >First programmable autonomous computing machine in which the input, output, software and hardware were all made of DNA molecules. >Can perform a billion operations per second with 99.8% accuracy • In 2004 an autonomous DNA computer that is capable of diagnosing cancerous activity within a cell, and then releasing an anti-cancer drug upon diagnosis is constructed by Prof. Shapiro & team. They claim in the journal Nature that they were successful.

Developments in DNA computation(continued) 

A DNA Sequence Design for Direct-Proportional Length-Based DNA Computing using DNASequenceGenerator is developed in Universiti Teknologi Malaysia in 2008.  A Method to Encrypt Information with DNA Computing has been suggested by Zheng Zhang, Xiaolong Shi, Jie Liu of Department of Control Science and Engineering, Huazhong Univ of Sci&Tech,China in 2008.

Conclusion 

DNA computers showing enormous potential, especially for medical purposes as well as data processing applications.



Many issues to be overcome to produce a useful DNA computer.

References 

www.news.nationalgeographic.com/news/2003/ 02/0224_030224_DNAcomputer.html  www.cnn.com  www.sciam.com/article.cfm?articleID=000A4F2 E-781B-1E5A-A98A809EC5880105  http://unisci.com/stories/20021/0315023.htm  www.howstuffworks.com  www.bbcworld.com  www.wikipedia.com  IEEE papers on DNA computing

Thank you…