1. Presented by:
Dan Mugan, Nathan Russell
Brian Sands, & Chad Corillo

3. Introduction

4. Advantages
 Performs millions of operations at same time
 Good for parallel computing
 Ability to use large amounts of working memory
 1 gram of DNA can hold 1 x 1014 MB of data
 Or 145 trillion CDs
 1 CD is 800 MB

5. Advantages
 Cheaper
 Lightweight
 1 lb of DNA has more computing power than all
computers ever made
 Low power used to keep in original state
 Has ability to solve hardest problems in a matter of
weeks

6.  Environmentally friendly
 Clean, readily available materials

7. Ethics
 Terrorism and Government Control
 Ability to release a virus to computers inside bodies
 If nanobots fail inside of body, it could destroy a persons
organs that rely upon the bot
 Overpopulation
 With this technology people will live longer creating a
higher demand on resources

8. Ethics
• Creation of superior race (cyborg)
– Ability to use biocomputers to enhance certain abilities
• Intelligence
• Physical abilities
• Age
– These people will outperform the have nots who cannot
purchase the technology
– Can be used like steroids but without the side effects

9. Ethics
 Computers taking over
 Biocomputers will eventually have the capability to solve
problems on their own without human intervention
 This could mean a takeover by a Terminator type
creation
 Would you put your life in the hands of a computer?
 Computers today are not trustworthy at all times
 Doctor malpractice

10. Disadvantages
• Molecular operations are not perfect
• 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.
• Sometimes there are errors in the pairing of DNA
strands
• Simple problems solved faster on electronic computers

11. Disadvantages
 Human assistance is required
 Time consuming lab procedures
 No universal method of data representation
 DNA has a half-life
 Solutions could dissolve away before end result is found
 Information can be untransmittable
 Current DNA algorithms compute successfully w/o
passing any information from one processor to the next
in a multiprocessor connection bus.

12. Medical Applications
 In 2004, a group in Israel claimed to have created a
DNA automaton that can diagnose symptoms of
cancer and administer a therapy
 In prostate cancer, and some others, diagnosis is based on
molecular signatures
 It senses messenger RNA and can detect the
abnormal mRNAs produced by genes involved in
certain types of lung and prostate cancer.
 An anticancer drug is released if an abnormal mRNA
is found
 It is also made of DNA
 Tumor related gene suppressed

13. Medical Applications
 DNA computers known as computational genes
would be integrated into the genetic material
already in the patients cells
 Computational genes are similar to ordinary gene
DNA markers
 They will be programmed to react to a certain input with
a certain output
 Replacement of coding for protein structure.
 Designed a computational DNA molecule that
would answer 5 yes or no questions
 Questions used to establish the typical markers of
whether or not prostate cancer was present

14. Medical Applications
 If 5 yes answers were received, then there would be a
release of the drug.
 The researchers successfully applied this to a test system
that recreates the typical molecular signatures of
prostate cancer in vitro
 similar treatment on a test tube model of small cell lung
cancer.
 This is what researchers hope is the beginning of the
future for smart drugs
 Roam the body by fixing disease on the spot
 It would sense a change in the environment and respond by
releasing biological molecules

15. Medical Applications
 West Nile
 Could be used to distinguish between the various viral
strains
 Diabetes
 Could monitor blood sugar levels and dispense insulin
when needed.

16. Medical Applications
 May be several decades before such a system is
operating inside the human body will become a reality
 Process of introducing genetic material into a person
would need to be considered carefully.
 Bodies reaction may not be easily predicted

17. Computational Gene Challenges
 Delivery of the DNA into cells and incorporation into
the patients' own DNA.
 Keeping them from being treated by the immune
system as foreign invaders.

18. Artificial Intelligence

19. Conclusion