Seminar On Dna Computing

SEMINAR ON DNA COMPUTING

Presentation Outline        

Basic concepts of DNA Origin of DNA Computing Solution for NP-Complete Problems Advantages of DNA Computing Problems with Adleman’s Experiment DNA Computers Current research Conclusion

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 set of DNA DNA is unique for each individual

Double Helix shape of DNA

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The two strands of a DNA molecule are anti parallel where each strand runs in an opposite direction. Complementary base pairs Adenine & Thymine Guanine & Cytosine Two strands are held together by weak hydrogen bonds between the complementary base pairs

Graphical Representation of inherent bonding properties of DNA

Instructions in DNA Sequence to indicate the start of an instruction

……… Instruction that triggers Hormone injection

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Instruction for hair cells

Instructions are coded in a sequence of the DNA bases A segment of DNA is exposed, transcribed and translated to carry out instructions

DNA Duplication

Protein Synthesis  DNA

 RNA  Proteins  actions

Basics and Origin of DNA Computing 

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

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With an appropriate setup and enough DNA, one can potentially solve huge problems by parallel search.

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

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

Dense Information Storage 

This image shows 1 gram of DNA on a CD. The CD can hold 800 MB of data.

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The 1 gram of DNA can hold about 1x1014 MB of data.

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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 to.

How Dense is the Information Storage? 

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with bases spaced at 0.35 nm along DNA, data density is over a million Gbits/inch compared to 7 Gbits/inch in typical high performance HDD. Check this out………..

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 !

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Check this out……. We Typically use

How extraordinary is the energy efficiency? 

Adleman figured his computer was running 2 x 1019 operations per joule.

NP Complete Problems 

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A hard NP problem is one in which the time required for algorithms to find a solution increases exponentially with the number of variables involved. A hard NP problem can eat up a lot of computer cycles if carried out by brute force. For example, the Hamilton path problem —commonly known as the traveling salesman problem —is a hard NP problem. If there are N cities in a Hamilton path problem, there are N!/2 possible paths, where N! is N factorial, which is the multiplication of every integer from 1 to N —for example, 4!= 1 x 2 x 3 x 4.

Inventor Of DNA Computing: Adleman 

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Adleman is often called the inventor of DNA computers. His article in a 1994 issue of the journal Science outlined how to use 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 a number of cities, going through each city only once. As you add more cities to the problem, the problem becomes more difficult. Adleman chose to find the shortest route between seven cities.

Steps for Adleman’s Experiment 

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Strands of DNA represent the seven cities. In genes, genetic coding is represented by the letters A, T, C and G. Some sequence of these four letters represented each city and possible flight path. These molecules are then mixed in a test tube, with some of these DNA strands sticking together. A chain of these strands represents a possible answer. Within a few seconds, all of the possible combinations of DNA strands, which represent answers, are created in the test tube. Adleman eliminates the wrong molecules through chemical reactions, which leaves behind only the flight paths that connect all seven cities.

Adleman’s Experiment 

Hamilton Path Problem (also known as the travelling salesperson problem) Darwin

Perth

Alice Spring

Brisbane

Sydney Melbourne Is there any Hamiltonian path from Darwin to Alice Spring?

Adleman’s Experiment (Cont’d) 

Solution by inspection is: Darwin  Brisbane  Sydney  Melbourne  Perth  Alice Spring

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BUT, there is no deterministic solution to this problem, i.e. we must check all possible combinations. Darwin Perth

Brisbane Alice Spring Sydney Melbourne

Adleman’s Experiment (Cont’d) •

Encode each city with complementary base vertex molecules Sydney - TTAAGG Perth - AAAGGG Melbourne - GATACT Brisbane - CGGTGC Alice Spring – CGTCCA Darwin - CCGATG

Adleman’s Experiment (Cont’d) •

Encode all possible paths using the complementary base – edge molecules Sydney  Melbourne – AGGGAT Melbourne  Sydney – ACTTTA Melbourne  Perth – ACTGGG etc…

Adleman’s Experiment (Cont’d) •

Merge vertex molecules and edge molecules. All complementary base will adhere to each other to form a long chains of DNA molecules Merge Solution with Solution with & vertex DNA edge DNA Anneal molecules molecules Long chains of DNA molecules (All possible paths exist in the graph)

Adleman’s Experiment (Cont’d)

 Darwin

The solution is a double helix molecule: Brisbane

Sydney

Melbourne

Perth

Alice Spring

CCGATG – CGGTGC – TTAAGG – GATACT – AAAGGG – CGTCCA TACGCC – ACGAAT – TCCCTA – TGATTT – CCCGCA Darwin Brisbane

Brisbane Sydney

Sydney Melbourne

Melbourne Perth Alice Spring Perth

The success of the Adleman DNA computer proves that DNA can be used to calculate complex mathematical problems. Three years after Adleman's experiment, researchers at the University of Rochester developed logic gates made of DNA. Currently, logic gates interpret input signals from silicon transistors, and convert those signals into an output signal that allows the computer to perform complex functions. But the logic gates made up DNA instead of using electrical signals to perform logical, rely on DNA code. They detect fragments of genetic material as input, splice together these fragments and form a single output.

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For instance, a genetic gate called the "And gate" links two DNA inputs by chemically binding them so they're locked in an end-to-end structure.

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The researchers believe that these logic gates might be combined with DNA microchips to create a breakthrough in DNA computing.

Operations  Melting

breaking the weak hydrogen bonds in a double helix to form two DNA strands which are complement to each other  Annealing

reconnecting the hydrogen bonds between complementary DNA strands

Operations (Cont’d) 

Merging mixing two test tubes with many DNA molecules

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Amplification DNA replication to make many copies of the original DNA molecules

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Selection elimination of errors (e.g. mutations) and selection of correct DNA molecules

Extraction 

given a test tube T and a strand s, it is possible to extract all the strands in T that contain s as a subsequence, and to separate them from those that do not contain it.

Spooling the DNA with a metal hook or similar device

Formation of DNA strands.

Precipitation of more DNA strands in alcohol

Advantages of a DNA Computer 

Parallel Computing- DNA computers are massively parallel.

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Incredibly light weight- With only 1 LB of DNA you have more computing power than all the computers ever made.

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Low power- The only power needed is to keep DNA from denaturing.

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Solves Complex Problems quickly- A DNA computer can solve hardest of problems in a matter of weeks.

Cont…… 

Perform millions of operations simultaneously.

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Generate a complete set of potential solutions.

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Efficiently handle massive amounts of working memory.

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cheap, clean, readily available materials.

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amazing ability to store information.

Current Research

Soft Molecular Computing 

DNA Computing utilizes the complex interaction of bio molecules and molecular biology to effect computation

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Lab experiments in DNA Computing are unreliable, inefficient, unscalable and expensive compared to conventional computing standards

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A critical issue in DNA Computing is to test protocols

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So we will describe a platform EDNA, to address this problem.

EDNA,integrated software platform 

Address the basic problems of reliability, efficiency and scalability for molecular protocols using DNA molecules.

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Allows to take advantage of digital computers to gain realistic insights on actual test tube performance of a protocol before they are carried out in the lab.

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It is a research tool that makes it possible to use the advantages of conventional computing to bring to DNA computing comparable levels of reliability and efficiency.

EDNA 

EDNA is object oriented and extensible, so that it can easily evolve as the field progresses.

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EDNA is therefore a research tool that makes it possible to use the advantages of conventional computing to make DNA computing reliable.

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EDNA includes graphical interfaces and click-and-drag facilities to enable easy use.

DNA Authentication 

Taiwan introduced the world's first DNA authentication chip.

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The first DNA chip in the world has finally been developed by Biowell Technology Inc. after two years of research.

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Inside the chip is synthesized DNA, which can be identified by a device similar to an identification card or a credit card reader.

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Suggestions have been made to make use of DNA chips on national identification cards in order to crack down on frauds using fake ID cards.

DNA Authentication 

The synthesized DNA inside the chip generates DNA signals which only the company's readers can detect and authenticate in two seconds.

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The DNA chip can also be used on passports, credit cards, debit cards, membership cards, driver's licenses, automobile license plates, CDs, VCDs, DVDs, notebooks, PDAs, computer software.

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In addition to the absolute security of the DNA authentication systems, the price of the DNA authentication product is comparable to that of IC chip.

DNA Chip

What are the challenges? 

Error: Molecular operations are not perfect.

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Reversible and Irreversible Error

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Efficiency: How many molecules contribute?

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Encoding problem in molecules is difficult

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Scaling to larger problems

What are the challenges for Computer Science? 

Discover problems DNA Computers are good at o o

Messy reactions as positive Evolvable, not programmable

Characterize complexity for DNA computations with bounded resources  New notions of what a “computation” is? 

What are the challenges for molecular biology?     

Develop computation-specific protocols Better understanding of basic mechanisms and properties Better characterization of processes Measures of reliability and efficiency Advanced understanding of biomolecules other than DNA and RNA

What developments can we expect in the near-term?     

Increased use of molecules other than DNA Evolutionary approaches Continued impact by advances in molecular biology Some impact on molecular biology by DNA computation Increased error avoidance and detection

What are the long-term prospects? 

Cross-fertilization among evolutionary computing, DNA computing, molecular biology, and computation biology

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Niche uses of DNA computers for problems that are difficult for electronic computers

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Increased movement into exploring the connection between life and computation?

LIMITATIONS

DNA Vs Electronic computers 

At Present,NOT competitive with the state-of-theart algorithms on electronic computers o

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Only small instances of HDPP can be solved.Reason?..for n vertices, we require 2^n molecules. Time consuming laboratory procedures. Good computer programs that can solve TSP for 100 vertices in a matter of minutes. No universal method of data representation.

Size restrictions 

Adleman’s process to solve the traveling salesman problem for 200 cities would require an amount of DNA that weighed more than the Earth.

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The computation time required to solve problems with a DNA computer does not grow exponentially, but amount of DNA required DOES.

Error Restrictions 

DNA computing involves a relatively large amount of error.

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As size of problem grows, probability of receiving incorrect answer eventually becomes greater than probability of receiving correct answer

Cont….. High cost is time.

Occasionally slower-Simple problems are solved much faster on electronic computers.

Reliability- There is sometime errors in the pairing of DNA strands

Some more………. 

Different problems need different approaches.

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requires human assistance!

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DNA in vitro decays through time,so lab procedures should not take too long.

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No efficient implementation has been produced for testing, verification and general experimentation.

THE FUTURE! 

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

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

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The University of Wisconsin is experimenting with chip-based DNA computers.

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

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

THANK YOU!!!!! It will take years to develop a practical, workable DNA computer. But…Let’s all hope that this DREAM comes true!!! Pratibha Rathore VIII Sem