Harker School

Beyond Silicon: The Evolution of Biological Computing

Cell-Processor

In 1965, Gordon Moore predicted that processing power should double every eighteen months.1 Traditionally, this rapid growth has been achieved by shrinking distances between transistors and shortening the distance that information needs to pass through.1 However, the miniaturization of processors and transistors will soon reach a physical barrier.2 With this knowledge, researchers have begun searching for new computing systems that take different approaches to achieving greater efficiency. Many possible computing models have been explored, including optical computing, quantum computing, and perhaps most interestingly, biological computing.

Biological computing is an altogether very new and very different approach. Rather than attempting to increase the speed of each individual operation, biological computing uses components of living organisms to perform computing tasks faster through massive parallelism, a technique that uses a large number of elements each performing smaller tasks.1 Many recent advances have demonstrated the potential of biological computing, even though research has only begun. For example, Adamatzi and Selim Aki at Queens University demonstrated the ability of slime molds to determine the most efficient paths across networks, and Swiss researchers have successfully programmed human cells to perform binary operations.3 Currently, the preeminent developments in biological computing have occurred in DNA computing. DNA fragments of varying lengths are placed in a solution along with ATP to power the reaction, and the results are analyzed by determining the length and sequence of the output DNA molecule.4 DNA computing allows for the storage of data in a four letter code – “A,” “T,” “C,” and “G” – which is capable of storing far more data more compactly than the binary digit storage of electronic computers.4 In a brilliant example showcasing the potential of DNA computing to revolutionize man-machine interactions, Ehud Shapiro at the Weizmann Institute harnessed DNA computing to diagnose cancerous activity from within the cell and then release an anti-cancer drug based upon the resulting output.4

Advances in biological computing foreshadow a massive revolution in computing technologies by removing physical limitations, improving parallel processing, increasing energy efficiency, and reducing toxicity.1 First, while traditional computational development has relied upon reducing the sizes of and distances between transistors, techniques that will soon face physical limitations, biological computing rapidly increases speed by using more effective parallel processing, which is able to perform 100 times more operations per second than conventional measures.1 Second, biological computing is more energy efficient, relying on energy stored chemically in ATP instead of conventional energy supplies.1 Third, the use of biological components greatly reduces the price and toxicity of computing components, as most biological components are readily available and non-toxic.1 And lastly, biological computing allows for a completely new approach to problem solving: rather than approaching problems sequentially like traditional computers, biological computing is a unique data structure focused upon parallel operations.4 Revolutionizing the computing industry would have groundbreaking impacts in all fields of science, research, technology, and society since computers are crucial for scientific advancement for all scientific and engineering fields.

The decreased toxicity, increased availability, and greater energy efficiency of biological computers may lead to massive benefits for the environment. Traditional computers are major contributors to our carbon footprint; by 2020, the carbon emissions from data centers and Internet services is expected to increase four-fold, surpassing even the carbon footprint of the aviation industry.5 In addition, the production of traditional computers requires enormous amounts of natural resources. A single silicon chip requires 1.6 kilograms of fossil fuels, 72 grams of chemicals, and 32 kilograms of water to manufacture, which is all together over 700 times the weight of the final product.6 The disposal of traditional computers is further complicated by the heavy metals they contain, especially lead, mercury, and cadmium, which can easily leak into and contaminate the environment.6 By replacing the need for silicon and other inorganic materials with readily available organic materials, biological computing can help reduce resource strain. Furthermore, the decreased toxicity allows for safer production, storage, and disposal than silicon-based computers. Finally, the improved energy efficiency of biological computing can allow for a decrease in global energy consumption, reducing the strain on fossil fuels and decreasing the amount of pollutants released into the environment due to energy production. This could help reduce damage to ecosystems, decrease biodiversity loss due to toxicity, and combat climate change by decreasing energy consumption.

In addition to advancing computing, biological computing also allows for unprecedented advances in medicine and biology by allowing closer integration with living material. Biological data is already used to control the chemicals synthesized by various organisms; the development of organic data processing and memory storage greatly compounds this synergy.1 As demonstrated by the earlier research done by Shapiro on cancer diagnoses and treatment, biological computers could provide a means to treat and diagnose genetically based illnesses from within living organisms.1 For instance, Adamatzky Aki, a leading researcher in DNA computing, has suggested the use of a biological implant to detect and treat breast cancer.3 In addition, biological computing could be used to link silicon-based computing and living organisms. Studies on eels have demonstrated that living things can be linked to robots and controlled, providing the ability for humans to study organisms in unprecedented ways and allowing for advances in interactive prosthetics.1  Biological computing could also allow the introduction of computing in harsher natural environments by mimicking the adaptive strategies of resilient life-forms.3 Overall, these advantages could radically change our ability to garner data for a variety of fields, including biology, animal behavior, and studies in extreme environments. In addition, intimate integration with biological tissue could revolutionize the treatment of cancer and other diseases, transform health care, and pave the way for artificially constructed or controlled organisms that create new opportunities in fields ranging from farming to prosthetics.

References

1. Fulk, Kevin. “Biological computing.” ISRC Future Technology Topic Brief. 2002.
2. Junnarkar, Sandeep. “Tomorrow’s Tech: The Domino Effect.CNET News. October 24, 2002.
3. Baer Adam. “Why living cells are the future of data processing.” PopSci. November 5, 2012.
4. Tagore, Somnath; Bhattacharya, Saurav;  Islam, Ataul; Islam, Lutful. “DNA Computation: Applications and Perspectives.Journal of Proteomics & Bioinformatics. June 29, 2010: 234-243.
5. Kanter, James. “The Computer Age and its Carbon Footprint.” New York Times. June 13, 2008.
6. Locklear, Fred. “The Environmental Impact of Computing.Ars Technica. Nov. 12, 2002.

Brandon Yang is a student at The Harker School. Follow The Triple Helix Online on Twitter and join us on Facebook.

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Discussion

2 comments for “Beyond Silicon: The Evolution of Biological Computing”

  • WRightStar

    As described by Mr Yang, biological computing will lead to architectures and programming paradigms
    which solve important new problems, and solve them in new ways. However, the field will have matured to cover all of the visions mentioned above before it begins to compete with high-powered traditional silicon machines at the work they do best. Never-the-less the amount of information processing required to create a mature adult from a fertilized egg is astronomical, and it is expressed in programming concepts which border on Magic. In any form, Life, especially multicellular Life, is the great mystery that drives Science and now it is beginning to drive Computer Science. Gödel’s Theorem will become trivial in comparison.

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