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NA ComputingNA ComputingBy: Libin Lukose Emmanuel

1NH05IS020

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Fundamentals aboutDNA Structure

DNA is Deoxyribo Nucleic Acid and is the buildingblock of all living beings

It is a polynucleotide and has a double helical structure

It is made of nucleotidesAdenine(A),Guanine(G),Thiamine(T) and Cytosine( C)

Adenine bonds only with Thiamine and Guanine bondsonly with Cytosine

The two helix are complimentary of each other

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Basics and Origin of DNAComputing In 1994, Leonard Adleman, scientist at the university of California, introduced the idea of using DNA to solve complex mathematical problems

Leonard Adleman proposed that the makeup of DNA and its multitude of possible combining nucleotides could have application in computational research techniques

DNA computing is utilizing the property of DNA for massively parallel computation

With an appropriate setup and enough DNA, one can potentially solve huge problemsby parallel search

Utilizing DNA for this type of computation can be much faster than utilizing aconventional computer

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What is DNA Computing

The field of DNA computing is concerned with the possibility ofperforming computations using biological molecules.

It is also concerned with understanding how complex biological

molecules process information here an attempt to gain insightinto new models of computation.

So, DNA computer can be defined as a computer that

computes using enzymes that react with DNA strands,causing reactions. These reactions act as a kind ofsimultaneous computing orparallel processing.

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How does it work?

Use specially coded DNA as initial conditions for biologicalreaction

DNA is taken as software and enzymes as hardware.

Natural enzymes duplicate DNA

Matching DNA base pairs attach to each other

Find answer in resulting soup of DNA strands

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Why is it interesting?Cross-discipline (CS meets Molecular Biology)

High data density

Massively parallel

Energy efficient

Potential to perform computation inside the body

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Dense InformationStorageThis 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 1x1014 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 wouldtake 163,000 centuries to listen to.

With bases spaced at 0.35 nm along DNA,data density is over a million Gbits/inchcompared to 7 Gbits/inch in typical high

performance HDD

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How enormous is theparallelism?

A test tube of DNA can contain trillions of strands. Eachoperation on a test tube of DNA is carried out on all strands inthe tube in parallel !

Enzymes work over many DNA molecules simultaneouslyproviding DNA Parallelism.

Each DNA strand represents a processor !

Desktop PC : 109 ops/sec

Supercomputer : 1012 ops/sec

1 mol of DNA : 1026 reactions(isnt amazing)

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How extraordinary is the

energy efficiency?Adleman figured out that his computer was running 2 x

1019 operations per joule.

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Inventor Of DNAComputing:

Leonard AdlemanAdleman is often called the inventor of DNA computers. His

article in a 1994 issue of the journal Science outlined how touse DNA to solve a well-known mathematical problem, called

the directed Hamilton Path problem, also known as the"traveling salesman" problem.

The goal of the problem is to find the shortest route between anumber of cities, going through each city only once. As youadd more cities to the problem, the problem becomes moredifficult. Adleman chose to find the shortest route betweenseven cities using a brute force approach.

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RAVELLING SALESMAN ALGORITHAVELLING SALESMAN ALGORITH

Los Angeles New York

Chicago

MiamiDallas

Source Destination

A hypothetical salesman tries to find a route through a set of cities so that hevisits each city only once

Adlemans Experiment

S i dl

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Steps in AdlemansSteps in Adlemansexperiment wouldexperiment would bebe

as follows:as follows:1)Generate all possible routes

2)

3)Select itineraries that start and end with the correct cities

4)

5)Select itineraries that contain the correct number of cities

6)7)Select itineraries that have a complete set of cities

G t ll ibl

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STEP I: Generate all possibleroutes

STRATEGY:1)Encode city names in short DNA sequences.

2)Encode itineraries by connecting the city sequence forwhich routes exist

Los Angeles GCTACG

Chicago CTAGTA

Dallas TCGTAC

Miami CTACGG

New York ATGCCG

City Encodings

Synthesizing short single stranded DNA by DNA SYNTHESIZER

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e n e ra tio n o f d iffe re n tItin e ra rie s

Route Encoding

Miami

New York

C T A

A T G

C G G

C C G

C G G A T G

G

Miami New York

C T A C G G A T G C CG

Miami to New York

G C C T A C

Hybridized DNA

C C T A C

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Output of Step I

Los Angeles New York

Chicago

MiamiDallas

Source Destination

G C T A C G

C T A G T A

A T G C C G

T C G T A C C T A C G G

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:T E P II elect itineraries thattart and end with the correctcities

Los Angeles

Source

New York

Destination

G C T A C G A T G C C G

C G A T G C T A C G G C

STARTPRIMER

ENDPRIMER

Polymerase Chain Reaction is iterative and uses an enzyme called polymerasePolymerase copies a section of single stranded DNA starting at the position ofthe primer, which is DNA complimentary to one end of the interested section.

Technique used is: POLYMERASE CHAIN REACTION (PCR)Allows to produce many copies of a specific sequence of DNA

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:TEP III elect itineraries thatontain the correct number ofcitiesSTRATEGY:Sort the DNA by length & select the DNA whose length equals to

five cities

DNA Starts here

Long DNA

Short DNA

+ VOLTAGE

- VOLTAGE

GelMa

trix

Gel Electrophoresis force the DNA througha gel matrix by using an electric field.

Generally DNA is vely charged moleculebut with constant charge density.

GEL slows down the DNA passing throughit at different rates depending on its length

producing DNA bands.

Technique used is: GEL ELECTROPHORESISUsed to resolve size of DNA

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:TEP IV elect itineraries thatave a complete set of cities

G A T C A TC G A T G C T A C G G CG A T G C CA G C A T G

G C T A C G C T A G T A T C G T A C C T A C G G A T G C C G

LA toCHICAGO CHICAGO toDALLAS DALLAS toMIAMI MIAMI toNEW-YORK

Affinity purification is done by attaching the compliment of the sequence in question to asubstrate like magnetic bead.The DNA which contains the sequence hybridizes with the complement sequence on thebeads

Graduated PCR can also be used if we already have the sequence of city encodings.

Technique used is: AFFINITY PURIFICATION

Uses HYBRIDIZATION of DNA

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First DNA computer

:-MAYA II

Stand for (Molecular Array of YES and AND logic gate )

Replacing the normally silicon-based circuits, this chip has DNAstrands to form the circuit

MAYA-II has more than 100 DNA circuits

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Applications

DNA sequencing

DNA fingerprinting

DNA mutation detection

The fabrication of nanoscale objects

The replacement of silicon devices

Design of expert systems

Medical diagnosis, drug discovery

To Solve NP-Complete Problems

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LIMITATIONS The computation time required to solve problems with a DNA computer does

not grow exponentially, but amount of DNA required DOES.

DNA computing involves a relatively large amount of error

High cost is time.

Different problems need different approaches.

Requires human assistance!

No efficient implementation has been produced for testing, verification andgeneral experimentation

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THE FUTURE!

Algorithm used by Adleman for the traveling salesman problem was simple.As technology becomes more refined, more efficient algorithms may bediscovered.

DNA Manipulation technology has rapidly improved in recent years, andfuture advances may make DNA computers more efficient.

The University of Wisconsin is experimenting with chip-based DNA

computers.

DNA computers are unlikely to feature word processing, emailing andsolitaire programs.

Instead, their powerful computing power will be used for areas of encryption,genetic programming, language systems, and algorithms or by airlineswanting to map more efficient routes. Hence better applicable in only some

promising areas.

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Conclusion

The paradigm of DNA computing has lead to a very important theoreticalresearch.

The beauty of DNA research trends is found in the possibility of mankindsutilization of its very life building blocks to solve its most difficult problems.

The field of DNA computing is still in its infancy and the applications for thistechnology are still not fully understood.

Is DNA computing viable perhaps, but the obstacles that face the field such asthe extrapolation and practical computational environments required are daunting.

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Queries?