Biocomputing in a Nutshell

The novel technology that Microsoft has been working on

What is it though?

NOT to be confused with computational biology. That’s the very first thing that you should know. Computational biology is about creating models of molecules in a “normal” computer. Just like you can use CAD software to 3D print stuff, you can also use other programs to visualize the structures of proteins, for example.
The point is that computational biology doesn’t involve the actual use of biomolecules, and thus, it doesn’t have to do much with what I’m about to tell you.

Using biomolecules like DNA or proteins to perform logical operations, or store digital data

Thinking of biology as a set of tools that can be leveraged for other, before unimaginable, purposes, is what I think biological computing is about.
Another perspective that we could stumble upon is thinking of unmodified organisms as entities that are already computers in some way.

Before the BioLaptop

We’ve mentioned that biocomputing is all about emulating technology, so I think it’s essential to first understand the basics of traditional computing. Don’t worry, I’m not that much of a “techy” person, so I won’t be going too deep.

The classical computer

Although by the end of this article, we may all disagree, Google defines the word computer as “An electronic device for storing and processing data, typically in binary form, according to instructions given to it in a variable program”.

Image credits

Engineering biology

Biologists discover and engineers create. Discovery is to exploration what engineering is to creation. It’s said that it’s easier to understand electronics because we created it. However, with biology, we just started studying life after it had a few billion years head start.

  1. Reproducibility: this is harder in biology, but key in engineering. Robotics and ML can help with this by automating lab procedures and better designing experiments
  2. Testing: without Key Performance Indicators, your project can go wrong. However, it can be challenging if you don’t know what you’ll discover. Ask “What can be measured?”
  3. Borrowing from other disciplines: just like borrowing the fundamentals of engineering from other disciplines to harness biology
  4. Reinventing the process itself: breaking the problem down into parts, and then breaking the process down into steps. Think long-term, to project and to plan forward

Biological Computing

Having been able to create logic gates by using DNA means that we have the building blocks to achieve much more complex tasks. Indeed, scientists have been able to solve interesting problems using biomolecules, including the Salesman Problem, and have even done Machine Learning with DNA! 🤯

DNA Computing

I’ll call Leonard Adleman the father of biocomputing. He was the first to demonstrate the use of DNA to solve the seven-point Hamiltonian path problem in 1994.
The computation in this experiment was done at a rate of 100 Teraflops or 100 trillion floating point operations per second. To have a reference, the world’s fastest supercomputer, Earth Simulator, runs at just 35.8 Teraflops.

Peptide Computing

Not the most interesting, personally. However, the parallel interactions of peptide sequences and antibodies have been used to solve some problems.


This specific topic doesn’t have to do a lot with what I consider to be biocomputing. I just think it’s important to mention it because it’s still really mind-blowing.


Artificial Intelligence is already a tremendously hot but complex topic. What if we were *already* able to do this with biology?


The main challenge that biological computing is facing right now is the cost of reading and writing DNA, as well as the lack of preciseness that these technologies still have.


Like the experts have mentioned, I think that biological computers won’t be replacing the ones that we already know. Biology will keep on working for biology, but that only means that will be creating more effective treatments and more accurate diagnostics, by programming life in a better way.

DNA Data Storage

For sure, biocomputing sounds exciting. Nevertheless, what I think is going to be more feasible, at least in the short term, and when trying to compete against electronics, is DNA data storage.

Data storage crisis

Image credits to Twist Bioscience

The science behind

Conceptually, storing data into DNA is simple. There are 6 main steps that one should follow:

Image credits to Twist Bioscience

DNA of Things (DoT)

YAAAS! This is one of the most exciting ways to do DNA data storage, in my opinion. You may recognize the name because of its electric equivalent: Internet of Things (IoT).

  1. Translate that into a DNA sequence (As, Cs, Gs, Ts)
  2. Synthesize that DNA (print it)
  3. 3D print a bunny (or any other object)
  4. Encapsulate DNA into the bunny
  5. Take a sample of the bunny (it can be any tiny piece of plastic that forms the bunny)
  6. Extract the DNA from that tiny piece
  7. Sequence that DNA (read it)
  8. Translate that DNA sequence into a binary sequence using the corresponding equivalence that we used at the beginning
  9. Have a computer read that binary sequence and do whatever we need to do with it ;)

Plants & other organisms

The first practical idea about using plants as storage media was proposed by Karin Fister and Iztok Fister Jr. in 2013 when the two were still undergraduate students!


The great great problem that I see for DNA Data Storage, is the fact that it can’t be used in our day-to-day lives, at least not yet. The reason for this, is that I’m sure that I’m not the only person on the planet who doesn’t have a DNA sequencer and synthesizer at home, and even if I did, I’d totally prefer using the cloud instead.


Exciting! That’s all I can say. As I’m getting more into the field, I’m feeling more convinced that DNA Data storage is going to be something that we’ll get to see more and more, as sequencing and synthesizing technologies improve.

Living Medicines

Image credits to GROW by Ginkgo

How though?

Remember the logic gates and electrical circuits that we were talking about and how we can also create genetic circuits?
Well, living medicines essentially follow that logic and instructions.

vs Quantum

What does quantum computing have to do with biological computing? Definitely a question that I never thought I’d have to answer.
The truth is, that both of them have shown enough potential to exceed the power of conventional digital computers, provided that technical difficulties are overcome.

Shoutouts to companies

If you’ve read other of my articles about biotech, you know that I’m rather enthusiastic about taking innovations out to the market. This section is dedicated to those innovators in super-big or small companies that are making a difference by accelerating the development of biocomputing technologies.

Grow Your Own Cloud

Having proved that plant data storage is possible, GYOC is a startup that does exactly that: it stores digital data into DNA, and then puts it inside of plants. There is no other thing in the universe that makes more sense to me at this moment.
The data crisis tells us that we are probably creating more data than the one we can store. The ecological crisis tells us that we need more plants producing oxygen. What solves these two problems at once? Storing data into plants!

Microsoft’s Station B

It’s not necessary to place this at the top, since it clearly stands out on its own. You also know that something could be “The Next Big Thing” when a unicorn is working on it.

This video is responsible for me getting into the field of biocomputing. It’s great!

Twist Bioscience

Last, but definitely not least, there is Twist. This company is already an outlier in all-things DNA. Of course that it had to work on DNA data storage as well. Fun fact, Station B is partnering with them!

Twist Bioscience!

In a Nutshell

That was a long article, but probably a short Introduction to Biocomputing. This is part of my “Learn” phase in my biocomputing journey, which means that I’ll be releasing more interesting and deeper content very soon.

the best way to predict the future is to create it — Abraham Lincoln

Ambitious teenager building innovative projects with Synthetic Biology and Artificial Intelligence

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