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Presented by:Dan Mugan, Nathan RussellBrian Sands, & Chad Corillo
Introduction
Advantages Performs millions of operations at same time    Good for parallel computing Ability to use large amounts of ...
Advantages Cheaper Lightweight    1 lb of DNA has more computing power than all     computers ever made Low power used...
 Environmentally friendly    Clean, readily available materials
Ethics Terrorism and Government Control    Ability to release a virus to computers inside bodies    If nanobots fail in...
Ethics• Creation of superior race (cyborg)   – Ability to use biocomputers to enhance certain abilities     •   Intelligen...
Ethics Computers taking over    Biocomputers will eventually have the capability to solve     problems on their own with...
Disadvantages• Molecular operations are not perfect• DNA computing involves a relatively large amount of  error• As size o...
Disadvantages   Human assistance is required   Time consuming lab procedures   No universal method of data representati...
Medical Applications In 2004, a group in Israel claimed to have created a DNA automaton that can diagnose symptoms of can...
Medical Applications DNA computers known as computational genes  would be integrated into the genetic material  already i...
Medical Applications If 5 yes answers were received, then there would be a  release of the drug. The researchers success...
Medical Applications West Nile   Could be used to distinguish between the various viral    strains Diabetes   Could mo...
Medical Applications May be several decades before such a system is operating inside the human body will become a reality...
Computational Gene Challenges Delivery of the DNA into cells and incorporation into the patients own DNA. Keeping them f...
Artificial Intelligence
Conclusion
Biological computers
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Biological computers

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Biological computers

  1. 1. Presented by:Dan Mugan, Nathan RussellBrian Sands, & Chad Corillo
  2. 2. Introduction
  3. 3. 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
  4. 4. 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
  5. 5.  Environmentally friendly  Clean, readily available materials
  6. 6. 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
  7. 7. 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
  8. 8. 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
  9. 9. 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
  10. 10. 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.
  11. 11. 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
  12. 12. 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
  13. 13. 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
  14. 14. 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.
  15. 15. 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
  16. 16. 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.
  17. 17. Artificial Intelligence
  18. 18. Conclusion

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