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What is being studied?

There are a wide variety of sub fields in DNA computing that are being explored:
  • Error correction and minimizing error in the biological process - Are there algorithms that we can use that will minimize the error that comes naturally in any lab biological lab process? How do we quantify the error that is produced? What methods do we use to do error correction? Can the orthodox methods of error correction that have already been established be applied to DNA computing?
  • Using DNA computing to break encryption standards - What are the issues that have hindered DNA computing from breaking encryption standards? What new algorithms can be developed to do so?
  • Adapting DNA for general purpose computing - Can DNA be used for general purpose computing? Will DNA computers ever replace desktops and computers as they are commonly used today? If not, what will be the more common application? How can DNA be used to simulate Turing Machines.
  • Automating the process with robots/chips (MEMS) - What are the ways the process of DNA computing can be mechanized? Is it viable to put DNA on chips or use robots to automatically conduct the biological processes? Can DNA be hybridized with silicon based architectures?
  • DNA Computational Theory - What are some new compuation paradigms that have come about that take advantage of DNA computing? What are splicing systems and self-organization? What algorithms take advantage of massively parallel properties of DNA. What are some evolutionary or genetic algorithms being developed?
  • Using DNA as in memory devices - How can DNA be used as tiny memory devices? What advantages might DNA have in being used for this purpose?
  • Solving "hard problems" that can not be solved by silicon computers
  • Solving the problem of reducing the amount of space (amount of DNA) used in molecular computations DNA and nano-assembly techniques. Although, DNA is massively parallel, it sacrifices space for time. How do we limit this sacrifice so that the amount of DNA used in algoritms is not as much.
  • Medical applications - How can DNA be "programmed" for medical uses (ie. fighting diseases and illnesses, genetic cures....)?