Seminar on DNA Computing

SEMINARON

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

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

Instructions are coded in 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 triggersHormone injection

Instruction for hair cells

………

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.

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

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

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.

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 would take 163,000 centuries to listen to.

How Dense is the Information Storage?

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 !

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

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

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

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)

Perth

Darwin

Brisbane

Sydney

Melbourne

Alice Spring

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

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

Perth

DarwinBrisbane

Sydney

Melbourne

Alice Spring

Adleman’s Experiment (Cont’d)

1. Encode each city with complementary base - vertex moleculesSydney - TTAAGGPerth - AAAGGGMelbourne - GATACTBrisbane - CGGTGCAlice Spring – CGTCCADarwin - CCGATG

Adleman’s Experiment (Cont’d)

2. Encode all possible paths using the complementary base – edge moleculesSydney Melbourne – AGGGATMelbourne Sydney – ACTTTAMelbourne Perth – ACTGGGetc…

Adleman’s Experiment (Cont’d)

3. Merge vertex molecules and edge molecules.

All complementary base will adhere to each other to form a long chains of DNA moleculesSolution with vertex DNA molecules

Solution with edge DNA molecules

Merge&

Anneal

Long chains of DNA molecules (All possible paths exist in the graph)

Adleman’s Experiment (Cont’d)

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

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.

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.

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

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

Operations (Cont’d)

Mergingmixing two test tubes with many DNA molecules

AmplificationDNA replication to make many copies of the original DNA molecules

Selectionelimination 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.

Formation of DNA strands.

Precipitation of more DNA strands in alcohol

Spooling the DNA with a metal hook or similar device

Advantages of a DNA Computer

Parallel Computing- DNA computers are massively parallel.

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

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

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

Cont……

Perform millions of operations simultaneously.

Generate a complete set of potential solutions.

Efficiently handle massive amounts of working memory.

cheap, clean, readily available materials.

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

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

A critical issue in DNA Computing is to test protocols

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.

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.

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.

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

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

DNA Authentication

Taiwan introduced the world's first DNA authentication chip.

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

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

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.

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.

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.

Reversible and Irreversible Error

Efficiency: How many molecules contribute?

Encoding problem in molecules is difficult

Scaling to larger problems

What are the challenges for Computer Science?

Discover problems DNA Computers are good ato Messy reactions as positiveo 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

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

Increased movement into exploring the connection between life and computation?

LIMITATIONS

DNA Vs Electronic computers

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

o Only small instances of HDPP can be solved.Reason?..for n vertices, we require 2^n molecules.

o Time consuming laboratory procedures.o Good computer programs that can solve TSP for 100

vertices in a matter of minutes.o 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.

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.

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

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

Cont…..

Some more……….

Different problems need different approaches.

requires human assistance!

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

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.

DNA Manipulation technology has rapidly improved in recent years, and future 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 and solitaire programs.

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