Ever wondered where we would find the new
material needed to build the next generation of
HUMAN BODY (including yours!)…….DNA
“Computation using DNA” but not “computation
Dr. Leonard Adleman is often called “The inventor
of DNA Computers”.
What is a DNA?
A nucleic acid that carries the genetic information in
DNA is composed of A (Adenine), C (Cytosine),
G (Guanine) and T (Thymine)
A DNA string can be viewed as a memory resource to
4 types of units (A,C,G,T)
Complementary units: A-T,C-G
Uniqueness of DNA
Why is DNA a Unique Computational Element???
Extremely dense information storage.
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
MB of data.
It can be defined as the use of biological molecules,
primarily DNA , to solve computational problems
that are adapted to this new biological format
Computers Vs DNA computing
DNA based Computers Microchip based Computers
Slow at Single Operations Fast at Single Operations
Able to simultaneously perform
Millions of operations
Can do substantially fewer
Huge storage capacity Smaller capacity
Why do we investigate about “other”
Certain types of problems (learning, pattern
recognition, fault-tolerant system, large set searches,
cost optimization) are intrinsically very difficult to
solve with current computers and algorithms
NP problems: We do not know any algorithm that
solves them in a polynomial time all of the current
solutions run in a amount of time proportional to an
exponential function of the size of the problem
Adleman’s solution of the Hamiltonian
Directed Path Problem(HDPP).
I believe things like DNA computing will eventually
lead the way to a “molecular revolution,” which
ultimately will have a very dramatic effect on the
world. – L. Adleman
An example of NP-problem: the Traveling
TSP: A salesman must go from the city A to the city
Z, visiting other cities in the meantime. Some of the
cities are linked by plane. Is it any path from A to Z
only visiting each city once?
An example of NP-problem: the
Traveling Salesman Problem
1. Code each city (node) as an 8 unit DNA string
2. Code each permitted link with 8 unit DNA strings
3. Generate random paths between N cities (exponential)
4. Identify the paths starting at A and ending at Z
5. Keep only the correct paths (size, hamiltonian)
Coding the paths
1, Atlanta – Boston:
(Hybridization and ligation between city molecules and intercity link molecules)
Filter the correct solutions
1.Identify the paths starting at A and ending at Z
PCR for identifying sequences starting with the last nucleotides of A and
ending at the first nucleotides of Z
2. Keep only the paths with N cities (N=number of cities)
3. Keep only those paths with all of the cities (once)
Antibody bead separation with each vertex (city)
The sequences passing all of the steps are the solutions
1.Generate Random paths
2.From all paths created in step 1, keep only those that
start at s and end at t.
3.From all remaining paths, keep only those that visit
exactly n vertices.
4.From all remaining paths, keep only those that visit
each vertex at least once.
5.if any path remains, return “yes”;otherwise, return
DNA Vs Electronic computers
At Present,NOT competitive with the state-of-
the-art algorithms on electronic computers
Only small instances of HDPP can be
solved.Reason?..for n vertices, we require 2^n
Time consuming laboratory procedures.
No universal method of data representation.
Ample supply of raw materials.
No toxic by-products.
Smaller compared to silicon chips.
Efficiency in parallel computation.
Danger of Errors possible
Assuming that the operations used by Adleman
model are perfect is not true.
Biological Operations performed during the
algorithm are susceptible to error
Errors take place during the manipulation of
DNA strands. Most dangerous operations:
The operation of Extraction
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
Satisfiability and Boolean Operations
Finite State Machines
Solving NP-hard problems
DNA Computing uses DNA molecules to
DNA Computing is a Massive Parallel
Computing because of DNA molecules
Someday, DNA Computer will replace the
silicon-based electrical computer
It will take years to develop a practical,
workable DNA computer.
But…Let’s all hope that this DREAM comes