BIOLOGICAL COMPUTERS

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BIO COMPUTERS
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INTRODUCTION

• Growing needs of mankind-Rapid Development.
• Rapid advancement in computer technology will
• lose its momentum when silicon chip reaches
  its full capacity miniaturization
• Solving complex problems which today's
  supercomputers are unable to perform in
  stipulated period of time.
• WHAT COULD BE A REMEDY TO THIS
  CONCERN?????

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BIOLOGICAL COMPUTERS
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What is Biological Computer?

• Biological Computers are computers which use
  synthesized biological components to store and
  manipulate data analogous to processes in the
  human body.
• The result is small yet faster computer that
  operates with great accuracy.
• Main biological component used in a Biological
  Computer is

DNA
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What is DNA?

• DNA Stands for DeOxyRiboNucleic Acid.
• A hereditary material found in almost all living
  organisms.
• Located inside the nucleus of a cell.
• Helps in long term storage of information.
• Information in DNA is stored as a code made of
  four chemical bases (A,T,G C).
• Order sequence of these bases determine the
  kind of information stored.

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Graphical Representation of Inherent Bonding
PropertiesofDNA
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What is a DNA Computer?

• DNA Computers are small, fast and highly
  efficient computers which includes the following
  properties-
• Dense data storage.
• Massively parallel computation.
• Extraordinary energy efficiency.

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How Dense is the Data 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..

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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

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How Extraordinary is the Energy
Efficiency?

• Modern supercomputers only operate at 109
  operations per joule.
• Adleman figured his computer was running
• 2 x 1019 operations per joule.

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Adleman-Inventor of Biological Computers

• His article released in 1994,described how to use
  DNA to solve a well-known mathematical problem,
  called the directed Hamilton Path problem.
• 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.

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Steps in Adlemans Experiment

• Strands of DNA represent the seven cities.
  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.

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Hamilton Path Problem
Is there any Hamiltonian path from
Darwin to Alice Spring?

• (also known as the travelling salesperson problem)

Darwin
Brisbane
Perth
Alice Spring
Sydney
Melbourne
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Adlemans Experiment (continued)

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

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Adlemans Experiment (continued)

• Encode all possible paths using the complementary
  base edge moleculesSydney ? Melbourne
  AGGGATMelbourne ? Sydney ACTTTAMelbourne ?
  Perth ACTGGGetc

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Adlemans Experiment (continued)

• Merge vertex molecules and edge molecules. All
  complementary base will adhere to each other to
  form a long chains of DNA molecules

Merge Anneal
Solution with edge DNA molecules
Solution with vertex DNA molecules
Long chains of DNA molecules (All possible paths
exist in the graph)
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Adlemans Experiment (continued)

• Select a path that starts with proper city and
  ends with final city.
• Select paths with correct number of cities.
• Select path which contains each city only once.

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Adlemans Experiment (continued)

• The solution is a double helix molecule
• Hence Adleman proved DNA can be used to solve
  complex problems.

Alice Spring
Perth
Melbourne
Sydney
Brisbane
Darwin
CCGATG CGGTGC TTAAGG GATACT AAAGGG
CGTCCA TACGCC ACGAAT TCCCTA TGATTT
CCCGCA
Darwin ?Brisbane
Brisbane ?Sydney
Sydney ?Melbourne
Melbourne ?Perth
Perth ?Alice Spring
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Conventional vs. Biological Computers
Conventional Biological
Component materials Inorganic, e.g. silicon Biological, e.g. DNA
Processing scheme Sequential and limited massively parallel Massively parallel
Current max. operations 1012 Op.s per sec. 1014 Op.s per sec.
Quantum effects a problem? Yes No
Toxic components? Yes No
Energy efficient? No Yes
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Applications

• Can be a general purpose tool for a variety of
  problems
• Many possible applications
• Pattern recognition
• Cryptography
• Evaluating gene sequence
• Medical Application developing disease
  treatments such as cancer

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Advantages of Biological Computers

• Parallel Computing- Biological 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.

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Advantages (Continued)

• 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.

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Limitations

• Error Molecular operations are not perfect.
• Efficiency How many molecules contribute?
• Encoding problem in molecules is difficult
• 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
• Reliability- There is sometime errors in the
  pairing of DNA strands
• DNA in vitro decays through time, so lab
  procedures should not take too long.

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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.

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THANK YOU!!!