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DNA as Data Center? What is DNA Calculation?

Hasnainistz

We live in an era of exponential data growth. Approximately 2.5 quintillion bytes of data are generated every day, and managing this massive volume presents a significant challenge. Traditional silicon-based storage media, such as hard drives, flash drives, and solid-state drives, have come a long way, but are rapidly approaching their physical limits. Enter the fascinating world of DNA computing, a field that presents a radically different approach to data storage and processing.

DNA molecule.

DNA Calculation: An Introduction

DNA computation takes advantage of the biological molecules within DNA to perform computational operations. The concept was first introduced by Leonard Adleman, a computer science professor at the University of Southern California, in 1994. DNA, the blueprint for life, is an incredibly dense and stable medium. One gram of DNA can theoretically store about 215 petabytes (215 million gigabytes) of data. It has the potential to revolutionize the way we store and process information.

How does DNA data archiving work?

In DNA data storage, digital data is converted into DNA sequences. The binary code (1s and 0s) that make up digital data is transformed into the four-letter DNA code A (adenine), T (thymine), G (guanine), and C (cytosine). The resulting DNA sequences are then synthesized, stored, and can be read back by sequencing the DNA and converting the A, T, G, C sequences back into 1s and 0s.

The potential impact of DNA data archiving

Here are some ways DNA computation could shape the world of technology:

  1. Huge storage capacity: The biggest advantage of DNA data archiving is its enormous density. As mentioned, a single gram of DNA can contain hundreds of millions of gigabytes of data. To put that into perspective, all of the world’s data could fit in a small room if stored in DNA.
  2. Longevity and stability: DNA can remain stable for thousands of years if properly stored. This is in stark contrast to traditional archival media which can degrade in a matter of decades.
  3. Energy efficiency: Writing and reading DNA requires chemical reactions, making the process much more energy efficient than electrically recharging the silicon cells in traditional storage media.
Large datacenters to store big data.

The road to feasibility

While the potential is immense, there are challenges to overcome before archiving DNA data becomes commercially viable. The cost of DNA synthesis and sequencing is currently prohibitive for mass use, and the process is relatively slow.

However, promising progress is being made in this area. For example, in 2012, a team from Harvard University stored 70 billion copies of their book (about 700 terabytes of data) in DNA. In 2017, Microsoft demonstrated the feasibility of archiving DNA data by encoding hello into DNA and converting it back into digital data. Advances in technology and economies of scale are expected to make archiving DNA data economically feasible in the future.

Leap into the future

As we look forward, the potential of DNA computation is incredibly exciting. Not only could it help manage the deluge of data we are currently facing, but it also opens avenues for new computational paradigms that leverage biological systems. DNA computing presents a beautiful blend of biology and computer science, marking a significant step towards sustainable and scalable data management.

To learn more, interested readers can explore courses like Introduction to Bioinformatics offered by the University of California, San Diego through Coursera, or DNA from Structure to Therapy from the University of Basel on edX.

In the evolving landscape of data storage and computation, DNA computation could very well be the game changer, ushering us into an era of biological data storage and processing.

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Image Source : medium.com

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