Date post: | 10-Aug-2015 |
Category: |
Documents |
Upload: | arunita-banerji |
View: | 159 times |
Download: | 0 times |
DNA computingBY ARUNITA BANERJI
What is DNA? Deoxyribo-neuclic-acid
Double stranded helix of nucleotides
Long polymers of millions of linked nucleotides
DNA is encoded with four bases :
A = Adenine
T = Thymine
G = Guanine
C = Cytosine
These bases are like 0’s and 1’s used in Silicon Computers.
Complements
Complement of AGGCT :
TCCGA
Complement of TAGGA :
ATCCT
Complement of GATTACCA :
CTAATGGT
Interesting facts
• DNA MOLECULE IS 1.7 METERS LONG
• STRETCH OUT ALL THE DNA IN YOUR CELLS AND YOU CAN REACH THE MOON 6000 TIMES!
Conception
Moore’s Law states that silicon microprocessors double in complexity roughly every two years.
Miniaturisation is reaching its limits
Intel scientists say it will happen in about the year 2018.
Require a successor to silicon.
DNA Computing
Around 1950 first idea (Precursor Feynman)
First important experiment 1994: Leonard Adleman
In only 5 grams of DNA we get around 1021 bases !
Each DNA strand represents a processor
Why DNA Computing?
To overcome the following conventional computing problem:
Limit of miniaturization
Particular range of speed
Why DNA computing?
High information density
1 bit can be stored in approximately one cubic nanometer. Others storage media, such as videotapes, can store 1 bit in 1,000,000,000,000 cubic nanometer.
Operations on DNA are massively parallel:
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.
DNA : Parallelism
Enzymes do not function sequentially over DNA.
Many copies of Enzymes can work on many DNA molecules simultaneously.
What is parallel computing? 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
Storage density
One gram of DNA can hold 1x1014 MB of data
Specifications
One pound of DNA can store more information
One cm3 of DNA can hold approx 10TB of data
DNA computer the size of a teardrop more powerful than supercomputer
Evolution of the DNA computer
First practical DNA computer unveiled in 2002. Used in gene analysis.MAYA-II ( Molecular Array of YES
and AND logic gate )
MAYA–Il has more than loo DNA circuits
Evolution of the DNA computer
• Self-powered DNA computer unveiled in 2003 by Ehud Shapiro
• First programmable autonomous computing machine in which the input, output, software and hardware were all made of DNA molecules
o Can perform 330 trillion operation/sec
o Can perform a billion operations per second with 99.8% accuracy.
“This re-designed device uses its DNA input as its source of fuel," said Ehud Shapiro, who led the Israeli research team
Evolution of the DNA computer
• Biological computer developed that could be used to fight cancers.
o ‘Designer DNA’ identifies abnormal and is attracted to it.
o The Designer molecule then releases chemicals to inhibit its growth or even kill the malignant cells.
o Successfully tested on animals.
Advantages of DNA computers
• There is always a plentiful supply of it.
• It is a cheap resource.
• DNA biochips can be made cleanly
• “Doctors in Cells”
• DNA computers are massively parallel in their computation.
o Solutions that would otherwise take months to compute could be found in hours.
o Excellent for NP problems such as the Travelling Salesman problem.
Doctors in cells
Travelling salesman problem
Each city is treated as a node
Encode city names in short DNA sequences. Encode path by connecting the city sequence for which routes exist which routes exist.
Chicago
New York
MiamiDallas
Los Angeles
Los Angeles
GCTACG
Chicago CTAGTA
Dallas TCGTAC
Miami CTACGG
New York ATGCCG
MiamiCTAGG
New YorkATGCCG
Miami To New YorkGCCTAC
MiamiCTAGG
New YorkATGCCG
Miami to New YorkGCCTAC
Los Angeles GCTACG
Chicago CTAGTA
Dallas TCGTAC
Miami CTACGG
New York ATGCCG
City Encoding
Route encoding
Hybridised encoding
DNA computer v/s conventional computer
DNA BASED COMPUTING SILICON BASED COMPUTING
Slow at individual operations Fast at individual operations
Can do billion operations simultaneously
Can do fewer operations simultaneously
Can provide huge memory in small space
Smaller memory
Setting up a problem may involve considerable preparations
Setting up of a requires keyword input
DNA is sensitive to chemical deterioration
Electronic data are vulnerable but can be backed up easily
Current problems with the DNA computer
• Not completely accurate at this moment in time• During an operation, there is a 95% chance a particular
DNA molecule will ‘compute’ correctly
• DNA has a half-life• Solutions could dissolve away before the end result is
found.
Conclusion
DNA computers showing enormous potential, especially for medical purposes as well as data processing applications.
Still a lot of work and resources required to develop it into a fully fledged product.
THANKS