dna based computing final2 7
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Sandipan Das
DNA Based Computing
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Outline
Introduction
Memory storage
Hamiltonian Path Problem(Adelman experiment)
Recent DNA technology
Evolution of DNA Computer
DNA V/s Silicon computer
Application
Benefits and limitation
Conclusion
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Need of DNA computer?
Moores 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. Intel
scientists say it will happen in about the year
2018.
Require a successor to silicon.
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What is DNA?
DNA stands for Deoxyribonucleic Acid
DNA represents the genetic blueprint of living
creatures
DNA contains instructions for assembling
cells
Every cell in human body has a complete setof DNA
DNA is unique for each individual
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Double Helix
Sides
Sugar-phosphate backbones
ladders
complementary base pairs
Adenine & Thymine
Guanine & Cytosine
Two strands are held together by
weak hydrogen bonds between the
complementary base pairs
Source: Human Physiology: From Cells to System
4thEd., L. Sherwood, Brooks/Cole, 2001, C-3
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Composed of four nucleotides(+ sugar-phosphate backbone)A AdenineT ThymineC CytosineG Guanine
Bond in pairsA TC G
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Instructions in DNA
Instructions are codedin a sequence of the DNA
bases
A segment of DNA is exposed, transcribed and
translated to carry out instructions
Sequence to indicate the
start of an instruction
Instruction that triggers
Hormone injectionInstruction for hair cells
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DNA Duplication
Source: Human Physiology: From Cells to System
4th Ed., L. Sherwood, Brooks/Cole, 2001, C-5
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Can DNA Compute?
DNA itself does not carry out any computation.
It rather acts as a massive memory.
BUT, the way complementary bases react with
each other can be used to compute things.
Proposed by Adelman in 1994
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DNA computers are the computers which using
enzymes as a program that processes on the DNAmolecules (input data)
Definition Of DNA Computing
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Dense Information Storage
This image shows 1 gram of DNA on aCD. The CD can hold 800 MB of data.
The 1 gram of DNA can hold about1x1014 MB of data.
Storage Capacity: Vol(1g ofDNA)=1cm3 , 18Mb/inch of Length(0.35nm Between Base Pairs)
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How enormous is the parallelism?
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
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Outline
Introduction
Memory storage
Hamiltonian Path Problem
(Adelman experiment)Recent DNA technology
Evolution of DNA Computer
DNA V/s Silicon computer
Application
Benefits and limitation
Conclusion
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Adlemans Experiment
Hamilton Path Problem(also known as the travelling salesperson problem)
Perth
Darwin
Brisbane
Sydney
Melbourne
Alice Spring
Is there any Hamiltonian path from Darwin to Alice Spring?
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Adlemans Experiment (Contd)
Solution by inspection is:Darwin Brisbane SydneyMelbourne Perth
Alice Spring
BUT, there is no deterministic solution to thisproblem, i.e. we must check all possible
combinations.
Perth
Darwin
Brisbane
Sydney
Melbourne
Alice Spring
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Adlemans Experiment (Contd)
1. Encode each city with complementary base -
vertex moleculesSydney - TTAAGG
Perth - AAAGGGMelbourne - GATACT
Brisbane - CGGTGC
Alice SpringCGTCCA
Darwin - CCGATG
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Adlemans Experiment (Contd)
2. Encode all possible paths using the
complementary baseedge moleculesSydneyMelbourneAGGGAT
Melbourne SydneyACTTTAMelbourne PerthACTGGG
etc
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Adlemans Experiment (Contd)
3. Marge vertex molecules and edge molecules.All complementary base will adhere to each other to
form a long chains of DNA molecules
Solution with
vertex DNA
molecules
Solution with
edge DNA
molecules
Marge
&
Anneal
Long chains of DNA molecules (All
possible paths exist in the graph)
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Adlemans Experiment (Contd)
The solution is a double helix molecule:
CCGATG CGGTGC TTAAGG GATACT AAAGGG CGTCCA
TACGCC ACGAAT TCCCTA TGATTT CCCGCA
Darwin Brisbane Sydney Melbourne Perth Alice Spring
DarwinBrisbane
BrisbaneSydney
SydneyMelbourne
MelbournePerth
PerthAlice Spring
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A.Product of the ligationreaction (lane 1),
PCR amplification of the
product of the ligation
reaction ( 2 thru 5)molecular weight marker
in base pairs (lane
6).
B. Graduated PCR of the productfrom step 3( 1 thru 6)
the molecular weight marker is
in lane 7.
NOTE: These figures relate to the graph
used by Dr. Adleman.
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C. Graduated PCR of the final product of the experiment,revealing the Hamiltonian Paths ( 1 thru 6 ).
The molecular weight marker is in lane 7.
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Operations
Meltingbreaking the weak hydrogen bonds in a double helix
to form two DNA strands which are complement to
each other
Annealingreconnecting the hydrogen bonds between
complementary DNA strands
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Operations (Contd)
Mergingmixing two test tubes with many DNA molecules
AmplificationDNA replication to make many copies of the original
DNA molecules
Selection
elimination of errors (e.g. mutations) and selection ofcorrect DNA molecules
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Outline
Introduction
Memory storage
Hamiltonian Path Problem
(Adelman experiment)Recent DNA technology
Evolution of DNA Computer
DNA V/s Silicon computer
Application
Benefits and limitation
Conclusion
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DNA Chip
Source: Stanford Medicine Magazine, Vol 19, 3 Nov 2002http://mednews.stanford.edu/stanmed/2002fall/translational-dna.html
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Chemical IC
Source: Tokyo Techno Forum 21, 21 June 2001http://www.techno-forum21.jp/study/st010627.htm
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Outline
Introduction
Memory storage
Hamiltonian Path Problem
(Adelman experiment)Recent DNA technology
Evolution of DNA Computer
DNA V/s Silicon computer
Application
Benefits and limitation
Conclusion
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Evolution of the DNA computer (1)
Began in 1994 when Dr. Leonard Adleman
wrote the paper Molecular computation of
solutions to combinatorial problems.
He then carried out this experiment
successfully although it took him days to do
so!
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Evolution of the DNA computer (2)
DNA computers moved from test tubes onto
gold plates.
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Evolution of the DNA computer (3)
First practical DNA computer unveiled in 2002.
Used in gene analysis.
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Evolution of the DNA computer (4)
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.
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Evolution of the DNA computer (5)
Biological computer developed that could be
used to fight cancers.
Designer DNA identifies abnormal and is
attracted to it.
The Designer molecule then releases chemicals to
inhibit its growth or even kill the malignant cells.
Successfully tested on animals.
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Outline
Introduction
Memory storage
Hamiltonian Path Problem
(Adelman experiment)Recent DNA technology
Evolution of DNA Computer
DNA V/s Silicon computer
Application
Benefits and limitation
Conclusion
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DNA COMPUTER Vs SILICON COMPUTER
Feature DNA COMPUTER SILICON COMPUTER
Miniaturization Unlimited Limited
Processing Parallel Sequential
Speed Very fast Slower
Cost Cheaper Costly
Materials used Non-toxic Toxic
Size Very small Large
Data capacity Very large Smaller
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Outline
Introduction
Memory storage
Hamiltonian Path Problem
(Adelman experiment)Recent DNA technology
Evolution of DNA Computer
DNA V/s Silicon computer
Application
Benefits and limitation
Conclusion
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APPLICATIONS
DNA chips
Genetic programming
Pharmaceutical applications
Cracking of coded messages
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Outline
Introduction
Memory storage
Hamiltonian Path Problem
(Adelman experiment)Recent DNA technology
Evolution of DNA Computer
DNA V/s Silicon computer
Application
Benefits and limitation
Conclusion
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ADVANTAGES
Perform millions of operations simultaneously;
Conduct large parallel processing
Massive amounts of working memory;
Generate & use own energy source via the input.
Four storage bits A T G C .
Miniaturization of data storage
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LIMITATIONS
DNA computing involves a relatively large amount of error
Requires human assistance!
Time consuming laboratory procedures. No universal method of data representation.
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Outline
Introduction
Memory storage
Hamiltonian Path Problem
(Adelman experiment)Recent DNA technology
Evolution of DNA Computer
DNA V/s Silicon computer
Application
Benefits and limitation
Conclusion
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Conclusion
Many issues to be overcome to produce a
useful DNA computer.
It will not replace the current computers
because it is application specific, but has a
potential to replace the high-end research
oriented computers in future..
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Outline
Introduction
Memory storage
Hamiltonian Path Problem
(Adelman experiment)Recent DNA technology
Evolution of DNA Computer
DNA V/s Silicon computer
Application
Benefits and limitation
Conclusion
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References
Molecular Computation of Solutions to Combinatorial
Problems,L.M. Adleman,Science Vol.266 pp1021-1024,
11 Nov 1994
Computing With Cells and Atomsan introduction to
quantum, DNA and membrane computing, C.S. Calude andG. Paun, Taylor & Francis, 2001
The Cutting Edge Biomedical Technologies in the 21st
Century, Newton, 1999
Human Physiology: From Cells to Systems 4thEd.,L.Sherwood, Brooks/Cole, 2001
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