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