Published By: University of Manchester, 3/1/2017
Researchers from the University of Manchester have demonstrated that it is possible to build a super-fast self-replicating computer. Because it is composed of DNA molecules rather than electrical circuitry, when presented with a choice, such a computer can replicate itself to simultaneously compute the solutions. Demonstrating that this (previously only theoretical) machine is physically possible opens up new possibilities in the future of scientific computing.
Flesch-Kincaid Grade Level of Article: 14.7
Extended Discussion Questions
- What are some potential uses of a DNA computer that can compute faster than today’s electronic computers, using far less energy?
- Based on what you’re learning in this class, what kinds of problems are most difficult to deal with now because of the computation time required? How could DNA computing address those issues?
- In particular, how might the lower energy requirements change who can compute what when?
- The article compares DNA-based computers with computers composed of electronic circuits. Could changing the physical makeup of a computer totally alter society’s general understanding of what computing is/can be? Why or why not?
- In 2012, scientists were able to cram roughly 700 terabytes of data in a single gram of DNA, demonstrating its use as a storage medium. (In their words, “14,000 50-gigabyte Blu-ray discs…in a droplet of DNA that would fit on the tip of your pinky.”) What does this mean for the potential size of a DNA computer?
“Harvard Cracks DNA Storage, Crams 700 Terabytes of Data Into a Single Gram”
Published By: Extreme Tech, 8/17/2012 || View the Article
Provides some insight into advancements in DNA as a storage medium.
Relating This Story to the CSP Curriculum Framework
Global Impact Learning Objectives:
- LO 7.2.1 Explain how computing has impacted innovations in other fields.
Global Impact Essential Knowledge:
- EK 7.2.1B Scientific computing has enabled innovation in science and business.
Banner Image: “Network Visualization – Violet – Offset Crop“, derivative work by ICSI. New license: CC BY-SA 4.0. Based on “Social Network Analysis Visualization” by Martin Grandjean. Original license: CC BY-SA 3.0.