A Unique Data Structure
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Transcript of A Unique Data Structure
Ashish Gupta 98131
Ashish Gupta 98130
Unremarkable Problem , Remarkable Technique
Operations in a DNA Computer
DNA : A Unique Data Structure !
Pros and Cons
Steps of His Experiement
Major Breakthrough : Adleman’s Experiment
DNA vs Silicon
Conclusion – What does the future hold ?
1994 , Leonard M. Adleman solved: An unremarkable problem , A remarkable technique
The Problem : Hamiltonian Path Problem
The Significance:Use of DNA to solve computation problems Computation at molecular levels !DNA as a data structure !Massively Parallel Computation
DNA Structure Double-stranded molecule twisted into a helix Sugar Phosphate backbone Each strand connected to a complimentary strand Bonding between paired nucleotides :
Adenine and Thymine , Cytosine and Guanine
Data Storage Data encoded as 4 bases : A,T,C,G Data density of DNA
One million Gbits/sq. inch ! Hard drive : 7 Gbits per square inch
Double Stranded Nature of DNA Base pairs – A and T , C and G S is ATTACGTCG then S' is TAATGCAGC Leads to error correction !
DNA Non Von Neuman , stochastic machines ! Approach computation in a different way Performance of DNA computing
Affected by memory and parallelism Read write rate of DNA – 1000 bits/sec
Silicon Von Neumann Architecture Sequential : "fetch and execute cycle" “the inside of a computer is as dumb as hell, but it goes like mad!”
Richard Feynman
DNA Operations Fundamental Model Of computation : Apply a sequence of operations
to a set of strands in a test tube Extract , Length , Pour , Amplify , Cut , Join, Repair, and many others ! Many copies of the enzyme can work on many DNA molecules
simultaneously ! Massive power of DNA computation : Parallel Computation
CPU Operations Addition, Bit-Shifting, Logical Operators (AND, OR, NOT NOR)
Leonard Adleman of the University of Southern California shocked the science world in 1994
He solved a math problem using DNA – The Hamiltonian Path Problem – Published the paper “Molecular Computation of Solutions of Combinatorial Problems” in 1994 in Science
The field combines computer science, chemistry, biology and other fields.
Prompted an "explosion of work," David F. Voss, editor of Science magazine
Exhaustive Search Branch and Bound 100 MIPS computer : 2 years for 20 cities ! Feasible using DNA computation
10^15 is just a nanomole of material Operations can be done in parallel
ExampleProblem
Generate all the possible paths and then select the correct paths : Advantage of DNA approach
Select paths that contain each city only once
Steps taken by Adleman
Select paths with the correct number of cities
Select paths that start with the proper city and end with the final city
Generate all possible routes
StrategyEncode city names in short DNA sequences. Encode paths by
connecting the city sequences for which edges exist.
Process ( Ligation Reaction )Encode the CityEncode the EdgesGenerate above Strands by DNA synthesizerMixed and Connected together by enzyme - ligase
Random routes generated by mixing city encoding with the route encoding.
To ensure all routes , use excess of all encoding ( 1013 strands of each type )
Numbers on our side (Microscopic size of DNA)
After This StepWe have all routes between various cities of various lengths
Process (Polymerase Chain Reaction) Allows copying of specific DNA Iterative process using enzyme Polymerase Working : Concept of Primers Use primers complimentary to LA and NY
StrategyCopy and amplify routes starting with LA and ending with NY
After this StepHave routes of various lengths of LA….NY
Process (Gel Electrophoresis) force DNA through a gel matrix by using an electric field gel matrix is made up of a polymer that forms a meshwork of linked
strands
StrategySort the DNA by length and select chains of 5 cities
After This StepSeries of DNA bands –> select DNA with 30 bases
Process (Affinity Purification) Attach the complement of a city to a magnetic bead
Hybridizes with the required sequence Affinity purify five times (once for each city)
StrategySuccessively filter the DNA molecules by city, one city at a time
End resultPath which start in LA, visit each city once, and end in NY
Alternate Method : Graduated PCR Series of PCR amplifications done Primer corresponding to LA and one other city Measure length of sequence for each primer pair Deduce position of city in the path
One MethodSimply sequence the DNA strands
Speed1014 operations per second100x faster than current supercomputers !
Energy Efficiency2 x 1019 operations per joule. Silicon computers use 109 times more energy !
Memory1 bit per cubic nanometer1012 times more than a videotape !
Amount Scales Exponentially For a 200 city HP problem , amount of DNA required > Mass of
earth !
Stochastically driven process -> high error rates Each step contains statistical errors Limits the number of iterations
Current Trends Richard Lipton , Georgia Tech Surface DNA Techniques – U of Wisconsin 2010 – The first DNA chip will be commercially available
Huge advances in biotechnology DNA sequencing Faster analysis techniques : DNA chips
DNA : Molecule of the century Might be used in the study of logic, encryption, genetic
programming and algorithms, automata, language systems.
Molecular Computation of Solutions to Combinatorial
Computing Problems Leonard M. Adleman , Department of Computer Science,
University of Southern California , 1994
On the Computation Power of DNA Dan Boneh , Christoper Dunworth , Richard J. Liption
Department of Computer Science,Princeton University1996
DNA Computing : A Primer Will Ryu