Silent Sound Tech 4df

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Bhujbal Knowledge City

METs Institute Of EngineeringAdgaon, Nashik-422003.

ACADEMIC YEAR 2011-2012.

ASEMINAR

ON

DNA COMPUTING.

SUBMITTED IN

DEPARTMENT OF MCA

GUIDED BY

Prof. Swapnil.Kulkarni

PRESENTED BY

Mr. Sagar.Gorla

SYMCA

ROLL NO:-22


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Bhujbal Knowledge City

METs Institute Of EngineeringAdgaon,Nashik-422003.

Affiliated to

University Of Pune

Department Of Master of Computer Application

CERTIFICATE

This is to certify that seminar entitled

DNA COMPUTING.

Has satisfactorily completed by

Mr. Sagar.Gorla

In partial fulfillment of term work for

Degree in Master of Computer Application

For the academic year 2011-2012

(Prof.Swapnil Kulkarni) (Prof.Aruna Deogire)

Seminar Guide H.O.D.


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Acknowledgements

Every work is source which requires support from many people and areas. It gives me

proud privilege to complete the seminar on DNA Computing. under valuable guidance

and encouragement of my guide Prof. Swapnil Kulkarni.

I am also extremely grateful to our respected H.O.D.(MCA Dept.) Prof.Aruna

Deogire and Prof.Apeksha Gawande(Seminar Coordinator) for providing all facili-

ties and every help for smooth progress of seminar.

I would also like to thank all the Staff Members of MCA Department for timely

help and inspiration for completion of the seminar.

At last I would like to thank all the unseen authors of various articles on the

Internet, helping me become aware of the research currently ongoing in this field and all

my colleagues for providing help and support in my work.

Mr. Sagar.Gorla

S.Y.M.C.A.


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Abstract

Silicon microprocessors have been the heart of computing world for more than forty

years. Computer chip manufacturers are furiously racing to make the next micropro-

cessor that will topple speed records and in the process are cramming more and moreelectronic devices onto the microprocessor. Sooner or later the physical speed and minia-

turization limits of silicon microprocessors is bound to hit a wall. Chipmakers need a new

material to produce faster computing speed with fewer complexities. You wont believe

where scientists have found this new material. DNA, the material our genes are made of,

is being used to build the next generation of microprocessors. Scientists are using this

genetic material to create nano-computers that might take the place of silicon computers

in the next decade..

A nascent technology(nascent is used to make transformers and inductors ) thatuses DNA molecules to build computers that are faster than the worlds most powerful

human-built computers is called DNA computing. Molecular biologists are beginning to

unravel the information processing tools such as enzymes, copying tools, proofreading

mechanisms and so on, that evolution has spent millions of years refining. Now we are

taking those tools in large numbers molecules and using them as biological computer

processors..

DNA computing has a great deal of advantage over conventional silicon-based com-

puting. DNA computers can store more than 10 trillions. DNA molecules can fit intoarea no larger than 1 cubic centimeter . DNA computers have the ability to work in a

massively parallel fashion, performing many calculations simultaneously. DNA molecules

that provide the input can also provide all the necessary operational energy. DNA com-

puting has made a remarkable progress in almost every field. It has found application

in fields like biomedical, pharmaceutical, information security, cracking secret codes,

etc.Scentists and researchers believe that in the foreseeable future DNA computing could

scale up to great heights..


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Contents


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List of Figures


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Chapter 1

Introduction to DNA

DNA Computer can store billions of times more information then your PC hard

drive and solve complex problems in a less time. We know that computer chip manufac-

turers are racing to make the next microprocessor that will more faster. Microprocessors

made of silicon will eventually reach their limits of speed and miniaturization. Chips

makers need a new material to produce faster computing speeds.

To understand DNA computing lets first examine how the conventional computer

process information. A conventional computer performs mathematical operations by

using electrical impulses to manipulate zeroes and ones on silicon chips. A DNA computer

is based on the fact the information is ?encoded? within deoxyribonucleic acid (DNA)

as patterns of molecules known as nucleotides. By manipulating the how the nucleotides

combine with each other the DNA computer can be made to process data. The branch

of computers dealing with DNA computers is called DNA Computing.

The concept of DNA computing was born in 1993, when Professor Leonard Adleman,a

mathematician specializing in computer science and cryptography accidentally stumble

upon the similarities between conventional computers and DNA while reading a book by

James Watson. A little more than a year after this, in 1994, Leonard M. Adleman, a

professor at the University of Southern California, created a storm of excitement in the

computing world when he announced that he had solved a famous computation problem.

This computer solved the traveling salesman problem also known as the ?Hamiltonian

path problem, which is explained later. DNA was shown to have massively parallel pro-

cessing capabilities that might allow a DNA based computer to solve hard computational

problems in a reasonable amount of time.

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Chapter 2

Structure of DNA

This structure has two helical chains each coiled round the same axis (see dia-

gram). We have made the usual chemical assumptions, namely, that each chain consists

of phosphate diester groups joining -D-deoxyribofuranose residues with 3,5 linkages.

The two chains (but not their bases) are related by a dyad perpendicular to the fibre

axis. Both chains follow right- handed helices, but owing to the dyad the sequences of

the atoms in the two chains run in opposite directions. There is a residue on each every

3.4 A. in the z-direction. We have assumed an angle of 36 between adjacent residues in

the same chain, so that thestructure repeats after 10 residues on each chain, that is, after

34 A. The distance of a phosphorus atom from the fibre axis is 10 A. As the phosphates

are on the outside, cations have easy access.

Figure 2.1: Structure Of DNA

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The structure is an open one, and its water content is rather high. At lower

water contents we would expect the bases to tilt so that the structure could become morecompact.

The novel feature of the structure is the manner in which the two chains are held

together by the purine and pyrimidine bases. The planes of the bases are perpendicular

to the fibre axis. The are joined together in pairs, a single base from the other chain,

so that the two lie side by side with identical z-co-ordinates. One of the pair must be a

purine and the other a pyrimidine for bonding to occur.

The hydrogen bonds are made as follows : purine position 1 to pyrimidineposition 1 ; purine position 6 to pyrimidine position 6.

If it is assumed that the bases only occur in the structure in the most plausible

tautomeric forms (that is, with the keto rather than the enol configurations) it is found

that only specific pairs of bases can bond together. These pairs are : adenine (purine)

with thymine (pyrimidine), and guanine (purine) with cytosine (pyrimidine). In other

words, if an adenine forms one member of a pair, on either chain, then on these as-

sumptions the other member must be thymine ; similarly for guanine and cytosine. The

sequence of bases on a single chain does not appear to be restricted in any way. However,

if only specific pairs of bases can be formed, it follows that if the sequence of bases on

one chain is given, then the sequence on the other chain is automatically determined.

It has been found experimentally (3,4) that the ratio of the amounts of ade-

nine to thymine, and the ration of guanine to cytosine, are always bery close to unity for

deoxyribose nucleic acid.

It is probably impossible to build this structure with a ribose sugar in place of the

deoxyribose, as the extra oxygen atom would make too close a van der Waals contact.

The previously published X-ray data (5,6) on deoxyribose nucleic acid are insufficient

for a rigorous test of our structure. So far as we can tell, it is roughly compatible with

the experimental data, but it must be regarded as unproved until it has been checked

against more exact results. Some of these are given in the following communications.

We were not aware of the details of the results presented there when we devised our

structure, which rests mainly though not entirely on published experimental data and

stereochemical arguments.

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Chapter 3

DNA Computing (Deoxyribonucleic

Acid Computing):

DNA computing is a nascent technology that seeks to capitalize on the enormous informa-

tional capacity of DNA, biological molecules that can store huge amounts of information

and are able to perform operations similar to a computers through the deployment of

enzymes, biological catalysts that act like software to execute desired operations.

Scientists around the globe are now trying to marry computer technology and biology by

using natures own design to process information. Research in this area began with an ex-

periment by Leonard Adleman, a computer scientist at USC who surprised the scientific

community in 1994 by using the tools of molecular biology to solve a hard computational

problem.

A new version of a biomolecular computer developed at the Israel Institute of Technology

composed entirely of DNA molecules and enzymes. It can perform as many as a billion

different programs simultaneously.

This new computer is also autonomous; it processes calculations from beginning to end

without any human assistance. Other biomolecular computers

require humans to analyze and decipher results and perform intermediate tasks at differ-

ent points in the process before the computer can complete the operation.

Current computers consist of metal, plastic, wires and transistors. The manner in which

they process information is called linear because they conduct one computation at a time.

In the latest generation of computers, biological molecules replace all the components.

One advantage of these biomolecular computers over linear computers is their ability to

simultaneously carry out an enormous number of complex operations.

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Chapter 4

Interesting Facts

Figure 4.1: True Facts

1) DNA molecule is 1.7 meters long2) Stretch out the entire DNA in your cells and you could reach the moon 6000 times!

3) DNA is the basic medium of information storage for all living cells. It has contained

and transmitted the data of life for billions of years

4) Roughly 10 trillion DNA molecules could fit into a space the size of a marble. Since all

these molecules can process data simultaneously, you could theoretically have 10 trillion

calculations going on in a small space at once.

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Chapter 5

Where It All Started..?

The scientists at the forefront of the DNA computer revolution are a brilliant

breed indeed. It was all started by a professor of Computer Science at USC by the name

of Leonard M. Adleman, who utilized recombinant DNA to solve a simple Hamiltonian

path problem, more popularly recognized as a variant of the so-called traveling salesman

problem. In Adlemans version of the traveling salesman problem, or TSP for short,

a hypothetical salesman tries to find a route through a set of cities so that he visits each

city only once. As the number of cities increases, the problem becomes more difficult

until its solution is beyond analytical analysis altogether, at which point The Hamilto-

nian path problem, on a large scale, is effectively unsolvable by conventional computer

systems. Computers now solve such problems by trial and error. But if hundreds of

cities were involved, a conventional computer would require years to find the answer. A

DNA computer, on the other hand, tests all possible answers simultaneously, offering the

prospect of much speedier solutions.

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Chapter 6

How It Works..?

DNA is the major information storage molecule in living cells, and billions of

years of evolution have tested and refined both this wonderful informational molecule

and highly specific enzymes that can duplicate the information in DNA molecules DNA

computation is based on the fact that technology allows us to sequence (design) single

DNA strands which can be used as representations of bits of binary data. Technology also

allows us to massively amplify (reproduce) individual strands until there are sufficient

numbers to solve complex computational problems.Instead of using electrical impulses to

represent bits of information, the DNA computer uses the chemical properties of these

molecules by examining the patterns of combination or growth of the molecules or strings.

DNA can do this through the manufacture of enzymes, which are biological catalysts that

could be called the hardware used to execute the desired calculation.

1) DNA input molecule

2) The famous double-helix structure discovered by Watson and Crick consists of two

strands of DNA wound around each other. Each strand has a long polymer backbone

built from repeating sugar molecules and phosphate groups. Each sugar group is at-

tached to one of four bases. These four bases - guanine (G), cytosine (C), adenine (A)

and thymine (T) - form the genetic alphabet of the DNA, and their order or sequence

along the molecule constitutes the genetic code.In the cell, DNA is modified biochemical

by a variety of enzymes, which are tiny protein machines that read and process DNA

according to natures design. Just like a CPU has a basic suite of operations like addition,

bit-shifting, logical operators (AND, OR, NOT NOR), etc. that allow it to perform even

the most complex calculations; DNA has cutting, copying, pasting, repairing, and many

others. Many copies of the enzyme can work on many DNA molecules simultaneously.

This is the power of DNA computing, that it can work in a massively parallel fashion..

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Chapter 7

Advantages

1) Predictability :

DNAs chemical bases-adenine, thymine,cystosine, and guanine-hook up in a pre-

dictable manner:adenine always links with thymine and cytosine with guanine. Because

of regularity of pattern Adleman hypothesized that he could use molecules to process

data the same way PCs use microprocessors.

2) DNA Directions:

First, DNA is incredibly enery-efficinet.Take ligase, a molecule whose job is to stick

strands of DNA together. With just one joule of energy - the amount of energy a human

expends to lift one kilogram one meter, ligase molecules can perform 20x10 the 18th

operations, Adleman says. Thats a million times 20 operations. Such efficiency push

computing to new levels since electronics are limited by the amount of power-and the

heat it gives off-needed to run increasingly sophisticated operations.

3) Incredibly Cheap:

DNA is also a wonderful way to store information. One gram of genetic mate-

rial, which would occupy about one cubic centimeter, can hold as much information

as 1 trillion CDs, according to Adleman. Its also incredibly cheap: Commercial labs

sell a molecule of SNA for about one-thousand trillionth of a cent. The cost is about

30.foraDNAsequencebigenoughtocomputeon.IntelsellsitslatestP4chiopformorethan500.

DNA has been storing the blueprint of life for several billion years, says Adleman. Its

powers are untapped legacy for the 21st century.

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4) Half-Hour Test:

Researchers developed a process that synthesizes 10,000 different DNA strands that

are known to bond with genes related to specific diseases such as cancer. The strand are

numbered and mixed with fluid containing genes extracted from the patient. The fluid is

than tested to determine which genes are functioning in the patients cells by reading the

number of DNA strands that appear after a series of biochemical reactions. Researchers

can complete a single test in about 3 hours, about one-half to one-third time taken by

conventional biological methods.

Parallelism:

Electronic computers typically handle operations in a sequential manner. Of course, there

are multi-processor computers, and modern CPUs incorporate some parallel processing,

but in general, in the basic Von Neumann architecture computer [4], instructions are

handled sequentially. A von Neumann machine, which is what all modern CPUs are,

basically repeats the same fetch and execute cycle over and over again; it fetches an

instruction and the appropriate data from main memory, and it executes the instruction.

It does this many, many times in a row, really, really fast. The great Richard Feynman

[5], in his Lectures on Computation, summed up von Neumann computers by saying,the

inside of a computer is as dumb as hell, but it goes like mad! DNA computers, however,

are non-von Neuman, stochastic machines that approach computation in a different way

from ordinary computers for the purpose of solving a different class of problems. Typi-

cally, increasing performance of silicon computing means faster clock cycles (and larger

data paths), where the emphasis is on the speed of the CPU and not on the size of the

memory.

For example, will doubling the clock speed or doubling your RAM give you better perfor-

mance? For DNA computing, though, the power comes from the memory capacity and

parallel processing. If forced to behave sequentially, DNA loses its appeal. For example,

lets look at the read and write rate of DNA. In bacteria, DNA can be replicated at a

rate of about 500 base pairs a second. Biologically this is quite fast (10 times faster than

human cells) and considering the low error rates, an impressive achievement. But this is

only 1000 bits/sec, which is a snails pace when compared to the data throughput of an

average hard drive. But look what happens if you allow many copies of the replication

enzymes to work on DNA in parallel. First of all, the replication enzymes can start on

the second replicated strand of DNA even before theyre finished copying the first one.

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So already the data rate jumps to 2000 bits/sec. But look what happens after each

replication is finished - the number of DNA strands increases exponentially (2n after n

iterations). With each additional strand, the data rate increases by 1000 bits/sec. Soafter 10 iterations, the DNA is being replicated at a rate of about 1Mbit/sec; after 30

iterations it increases to 1000 Gbits/sec. This is beyond the sustained data rates of the

fastest hard drives.

5) Amazing Tool Test :

Thus, as the complexity of problems increases, the manual labour require for DNA

computing would outweight the benefits of super fast computation. DNA computers havethe potential to take computing to new levels, picking up where Moores law leaves off.

There are several advantages of using DNA instead of silicon:

1) As long as there are cellular organisms, there will always be a supply of DNA.

2) The large supply of DNA makes a cheap resource.

3) Unlike the toxic materials use to make traditional microprocessors, DNA biochips can

be made cleanly.

4) DNA computers are many times smaller than todays computer.

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Chapter 8

Applications

The potential applications of re-coding natural DNA into a computable form are many

and include:

1) DNA sequencing

2) DNA fingerprinting

3) DNA mutation detection

Figure 8.1: DNA Working

4) Development and miniaturization of biosensors, which could potentially allow com-

munication between molecular sensory computers and conventional electronic computers.5) The fabrication of nanoscale objects that can be placed in intracellular locations for

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6) The replacement of silicon devices with nanoscale molecular-based computational sys-

tems, and The application of biopolymers in the formation of novel nanostructured ma-

terials with unique optical and selective transport properties 7) DNA based models ofcomputation might be useful for simulating or modeling other emerging computational

paradigms, such as quantum computing, which may not be feasible until much later.

8) Evolutionary programming for applications in design or expert systems.

9) In theory, this technology could one day lead to the development of hybrid computer

systems, in which a silicon-based PC generates the code for automated laboratory- based

operations, carried out in a miniature lab in a box linked to the PC.

8.1 DNA Authentication Chip

Figure 8.2: DNA Chip

Taiwan introduced the worlds first DNA authentication chip.

1) Use of DNA chips on national identification cards in order to crack down on frauds

using fake ID cards.

2) The synthesized DNA inside the chip generates DNA signals which only the companys

readers can detect and authenticate in two seconds......

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8.2 DNA Can Treat Cancer

As in previous biological computers produced in Shapiros lab, input, output and soft-

ware are all composed of DNA, the material of genes, while DNA-manipulating enzymes

are used as hardware.

1)The newest versions input apparatus is designed to assess concentrations of spe-

cific RNA molecules, which may be overproduced or under produced, depending on the

type of cancer. Using pre-programmed medical knowledge, the computer then makes its

diagnosis based on the detected RNA levels.

In response to a cancer diagnosis, the output unit of the computer can initiate the

controlled release of a single-stranded DNA molecule that is known to interfere with the

cancer cells activities, causing it to self-destruct.

2) The strand are numbered and mixed with fluid containing genes extracted from the

patient. The fluid is than tested to determine which genes are functioning in the patients

cells by reading the number of DNA strands that appear after a series of biochemical

reactions.

Researchers can complete a single test in about 3 hours, about one-half to one-third

time taken by conventional biological

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Chapter 9

Limitations

However,there are certain shortcomings to the development of the DNA com-

puters: A factor that places limits on his method is the error rate for each operation.

Since these operations are not deterministic but stochastically driven, each step contains

statistical errors, limiting the number of iterations one can do successively before the

probability of producing an error becomes greater than producing the correct result.

Algorithms proposed so far use relatively slow molecular-biological operations. Each

primitive operation takes hours when you run them with a small test tube of DNA.

Some concrete algorithms are just for solving some concrete problems. Every Generating

solution sets, even for some relatively simple problems, may require impractically large

amounts of memory. Also, with each DNA molecule acting as a separate processor, there

are problems with transmitting information from one molecule to another that have yet

to be solved.

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Chapter 10

Latest Developments

Israeli scientists have devised a computer that is so tiny that a trillion of them could

fit in a test tube and perform can perform 330 trillion operations per second, more than

100,000 times the speed of the fastest PC with 99.8 percent accuracy. It is the first

programmable autonomous computing machine in which the input, output, software and

hardware are all made of biomolecules. Recently, the team has gone one step further.

In the new device, the single DNA molecule that provides the computer with the input

data also provides all the necessary fuel.

Classical DNA computing techniques have already been theoretically applied to a real

life problem: breaking the Data Encryption Standard, DES. Although this problem has

already been solved using conventional techniques in a much shorter time than proposed

by the DNA methods, the DNA models are much more flexible, potent, and cost effective.

Israeli scientists have devised a computer composed of DNA and enzymes. The enzyme

FokI breaks bonds in the DNA double helix, causing the release of enough energy for the

system to be self- sufficient. The design is considered a giant step in DNA computing

which could transform the future of computers,especially in pharmaceutical and biomed-

ical applications.

10.1 First Practical DNA Computer

Tokyo (July 3rd, 2002)

Olympus Optical Co. Ltd.

First commercially practical DNA computer

Specializes in gene analysis15


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Figure 10.1: First DNA Computer

Akira Toyama, an assistant professor at Tokyo University.

Standard gene analysis approach very time consuming (3 days)

Now done in 6hrs

Joint project called NovousGene Inc. spec in genome informatics.

Available for commercial use by researchers by 2003 sometime.

Two sections

Molecular Calculation component

DNA combination of molecules

Implements chemical reactions

Searches

Pulls out right DNA results

Electronic Calculation component

Executes processing programs

Analysis these results

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Chapter 11

DNA Vs Silicon Computer

Computing with DNA is a completely new method among the quantum computing. Al-

ternative to electronic/semiconductor technology, computing with DNA use biochemical

process based on DNA. Computing with DNA is also known as molecular computing, a

new approach to massive parallel computation based on groundbreaking work by Leonard

Adleman.

DNA plays the role of information storage in nature. DNA is the genetic material con-

taining the whole information of an organism to be copied into the next generation of the

species. DNA computing is a computational paradigm that uses synthetic (or natural)

DNA molecules as information storage media. The techniques of molecular biology, such

as polymerase chain reaction (PCR), gel electrophoresis, and enzymatic reactions, are

used as computational operators for copying, sorting, and splitting/concatenating the

information in the DNA molecules, respectively.

Computing with DNA molecules has many advantages over conventional computing

methods that utilize solid-state semiconductors. The properties of DNA computing com-

pared with conventional computers are summarized in Table 1. Though DNA computing

performs individual operations slowly, it can execute billions of operations simultaneously.

This is contrasted with the electronic digital computers where individual operations are

very fast; however, the operations are executed basically sequentially. The massive par-

allelism of DNA computing comes from the huge number of molecules, which chemically

interact, in a small volume. DNA also provides a high storage capacity since they encode

information on the molecular scale.

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Chapter 12

DNA Operation

While a number of equivalent formalizations exist, we follow the descriptions. Note that

the types of operations available are result of the capability of molecular biology rather

than the wishes of algorithms designers. Also note that this algorithms are performed

in constant time on testtubes which, for the sake of this discussion, may be of arbitrary

size this operations are :

1.Merge: This is the simple operations of combining the contents of two test tubes

in a third tube. ANNEAL: This is the process by which complementary strands of

DNA are paired to form the famous double-helix structure of Watson and crick. An-

nealing is achieved by cooling a DNA solution, which encourages pairing. Adleman

uses this in step 1 to generate all legal paths through the graph.

2.Melt: Melting is inverse operation of annealing. By heating the contents of a

tube, double-stranded DNA sequences are denatured, or separated into its two

single-stranded parts.

3.Saperation By Length: This operation allows one to remove from solution all the

DNA strands that contain a desired sequence. This is performed by generating the

strands whose complement is the desired sequence. This newly generated strand

is attached to magnetic substance which is used to extract the sequences after

annealing. This operation crux of Aldermans step 4 .

4.Copying/Amplification: Copies are made of DNA strands in a test tube. The

strands to be copied must have known sequences at both the beginning and end in

order for this operation to be performed.

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Chapter 13

Future Application

Figure 13.1: Future Posibilities

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Figure 13.2: Biomolecular Hardware

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Chapter 14

Conclusion

This is becoming one of the most exciting fields. Ill conclude this paper by just sharing

a vision for the future in which a single drop of water holds a veritable army of living

robots; in which people download software updates not for their computers, but for their

bacteria; and in which specially programmed cells course through a persons arteries,

monitoring blood sugar concentrations and keeping an eye out for cholesterol buildups.

These scenarios still belong to the realm of science fiction-but implanting computer pro-

grams into living creatures may not be far away. In the past few years, scientists have

taken the first steps towards creating a host of cellular robots that are programmed to

carry out tasks such as detecting and cleaning up environmental pollutants, tracking

down cancer cells in a body, and manufacturing antibiotics or molecular-scale electronic

components. These researchers have imported notions of electrical engineering-digital

logic, memory, and oscillators-into the realm of biology.

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Chapter 15

Bibliography

COMPUTING WITH DNA,Leonard M.Adleman,Scientific American, August 1998.

Martyn Amos (June 2005). Theoretical and Experimental DNA Computation.

http://www.dna.htm/

http://www.usc.edu/dept/molecular-science/papers/adleman-science.pdf

www.gene.com

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