Wait, What Is Biological Computing?
Not to be confused with computational biology
Recently, I decided to look into biological computing. After spending several hours learning about it, my biggest takeaway is that biological computing is a very big term for a very simple subject. Biological computation is made up of two large and important branches, DNA storage and biological computation, and both of them are dead simple.
DNA Storage
It takes a lot of information to make you. The full (diploid for you biology nerds out there) human genome is 6.4 billion base pairs long. That’s 6.4 billion A’s, C’s, G’s, and T’s just sitting in a space 6 micrometres across! On a computer hard drive, that’d take up 12.8 GB of space. If a grain of salt takes up 0.027 mm, you’d only need 20 grains of salt to store an entire terabyte with some space left over. So, does this mean it’s time to replace all your SSDs with DNA-based storage? Unfortunately, no. It takes a long time to write new DNA and a while to read DNA, and it’s also pretty expensive. Some companies are working on the price problem, but even so, you won’t be getting a DNA-based SSD for a long time, if ever.
So what is DNA storage useful for? Or, as one person I talked to put it, “Why not just put it on a USB in a safe? That sounds a lot easier than putting your data in a cactus.” There are two main benefits to DNA storage, other than its incredible storage density. Firstly, DNA is very stable. If stored correctly, data stored in DNA could last thousands of years. In theory, an expensive SSD could last 20–50 years. Furthermore, DNA is extremely common. The amount of data we generate is always increasing, and there’s only a limited supply of the kind of silicon we can use for SSDs. At current projections, we could run out of SSD-grade silicon by 2040. DNA could be a viable alternative to silicon for the kind of data that you want to keep around, but won’t need for a while. Already, companies are collaborating with Microsoft to do just this.
Biological Computation
DNA Storage sounds really important, right? Well, just wait till you hear about biological computation. It starts with a really simple observation; your cells are running code. Every cell in your body is running a complicated series of instructions that are critical to you not dying and stuff. For example, inside every cell is a little bit of DNA that says “If you get damaged, try to repair. If you can’t repair, self-destruct to stop yourself from becoming cancerous.” Biological computation is looking at all this and trying to find out how it works and how you can use it.
Some people think that biological computation could be used in the future as a powerful parallel computer able to solve problems that modern computers couldn’t. I’m a little skeptical about that idea, but that doesn’t matter. Even if biological computation doesn’t replace or augment our current computers, its other potential application will literally change the world as we know it. Think about it, if we understand the code cells are running, then we can fix it when it goes wrong. Take my earlier example. We have code running in all our cells that tell them to self-destruct if they get damaged. Sometimes cells get damaged in such a way that they ignore this code or this code is missing. Sometimes these cells start to multiply and evolve within our bodies until they become what we call cancer. If we understood the language of DNA, RNA, and proteins, we could write new “code” that would kill, or even fix the cancer cells. Once we figure out the programing language of life, the world will never be the same. Presumably, anyone who’s read this far believes in evolution. Imagine a world where we could intelligently design life. Look how far evolution’s got us and imagine how much farther we could take it. Imagine if you could grow an entire building from a single seed or a world where “you’ve got cancer” means you’ll have to take a day off work to get a couple of shots. This is the world that understanding biological computation and synthetic biology could give us.
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