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Comment by dnautics | Hacker News Reader

As someone who has a PhD in biochemistry and has been coding since age 5, I find the headline rediculous. You won't be computing in biology. Consider, a transistor is about 50-100 atoms wide. A protein, which cannot itself even be a minimal unit of compute, (maybe a molecular transistor like NiFe hydrogenase has a shot) is already bigger than that.

The things described in the article are not biology used for computation, but principles from CS applied to biology which has some validity. In one case I achieved strides in protein design by reducing the engineering cycle from months to days. Imagine hitting "compile" and having to wait a 72 hours to know your result. That's biology, even with a fast organism like yeast or e coli.

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"As someone who has a PhD in biochemistry and has been coding since age 5, I find the headline rediculous. You won't be computing in biology.... principles from CS applied to biology which has some validity."

I think it may be worth reminding people that modern-day computing is only a subset of computation, and not even necessarily a very large one. Computing with biology has extremely different characteristics from computing with modern computers, and the field of Software Engineering may not have much to say about it except in the vaguest of terms, but Computer Science may still have quite a lot to say about the limits of computation on this new substrate, how to do error correction, and all sorts of other things.

A computational formalism can easily be applied to something like an anti-body, and of course, anything larger than that. The primary thing that stops us is the fact that we have such a poor picture of what is going on that we don't have the data to create the formalisms correctly, nor machines (biological or otherwise) to manipulate such formalisms. But that's a human limitation and in some sense an engineering limitation, not a limitation of Computer Science.

Whatever we are coding in biology will be radically, radically different. Entire classes of squabbles in our industry become irrelevant; you won't get a concurrency choice (it's just "yes, all the time and everywhere"), there will be no meaningful debate over mutability (again, "yes all the time and everywhere"), "structured programming" is just meaningless since the entire concept of "scope" will be out the window. I don't know what it will look like. But I do know that whatever it is, quite a bit of Computer Science will still apply to it. Biological computing will not be immune to information theory. It won't be immune to complexity theory, although a whole new suite of classes will probably have to arise, and there will be a lot more probability in it (but recall that complexity theory already extensively uses that, so it's not like that's a new thing). And even software engineering won't be entirely tossed out... for instance, "leaky abstractions" will be an even bigger problem than they are for us now.

Computing with biology would be more like the "movable feast" computing architecture videos on YouTube. Prepare to be out-neckbearded if you watch them. Not sure how useful it would be. You don't want your bank account running on such a machine.

Part of what makes computing extremely useful is that it's a crutch that lets us do things our feeble human minds can't do. Logical purity, high numerical computation, immutable logging and provenance. At the edge we start to tolerate imprecision in some domains like hci and decision making when there's a premium attached to the process, that statistically (or if we're being cynical, projects the appearance of) yields an improvement, like being able to ingest high inhuman volumes of data, or where human interaction in the correction of erroneous processing is proximal and minimally effort inducing.

It will be different, but concurrency, mutability, structured programming, and scope are very relevant.

Concurrency: Not all genes are run at all times. Gene regulation can look a lot like code. Ex: if(curr_temp > DANGER_TEMP){temperature_defense_gene.activate()}.

Mutability & Scope: Cells that have the same genome can act very differently (all of your cells have ~the same DNA, but act very differently) and some cells in your body can change roles.

Structured Programming: Biological pathways use a lot of control flows. [1]

[1] https://en.wikipedia.org/wiki/Biological_pathway

While there's truth in the paradigm you advance, it's not anywhere near as binary or direct as you might me suggesting.

There's a ton of leakage and noise at most stages in biological pathways. Biology actually spends enormous amounts of effort to reduce the noise and leakage, but it's really hard to eliminate entirely.

Lets take the danger temp gene you use as an example. In bacteria that's mostly true, but even there what if we're low on nutrients? Or low on a particular nutrient? Or what if we start producing too much protein which is aggregating because the concentration is too high? Each cell is balancing all these concerns simultaneously, so even very simple biological circuits work/don't work in unexpected ways. What the OP is suggesting is that you're always concurrent with a huge number of different things going on that are far less isolated from your "process" than is traditionally the case in CS.

I agree that concurrency, mutability, scope, all that is relevant, but I think the OP's point that we don't have the theory on how those will apply in a biological context is correct.

Edit: for those interested, some papers on biological noise and the efforts cells use to reduce it:

https://arxiv.org/pdf/1610.00820.pdf https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4006352/ https://www.cell.com/molecular-cell/abstract/S1097-2765(12)0...

>Whatever we are coding in biology will be radically, radically different. ... But I do know that whatever it is, quite a bit of Computer Science will still apply to it.

Whenever there's an article about computation and the brain, or computation and biology, there's always someone showing up saying that the comparison is ridiculous because, hey, biology/computers are different.

To me, that's always felt like it was missing a huge point and I think your comment is one of the better ways I've seen it expressed. I hope we're getting closer to a point where we can eventually turn the page on this, and the Hubert Dreyfus-style arguments/declarations about what "computers can't do."

it's not about what "computers can't do", it's about what "biology can't do". Or more, appropriately, "what you could maybe push biology's round peg into a square hole and force it to do but we should probably stop and think about whether it's worth the effort".

> Imagine hitting "compile" and having to wait a 72 hours to know your result.

You mean, something like giving a deck of cards to a computing center operator and eventually getting back a printout of the outcome a few days later?

Yes, but e coli really is close to the limit of how fast you can go. They're rather like tribbles, before they are done splitting, the next generations dna has already started duplicating. The DNA copy time is ~40 minutes and the dividing time is prot close to 30.

Clickbait aside, I think there are vast possibilities for DNA to be used as a fabrication tool. Imagine a seed you could plant and it would rapidly grow in the shape of a house, using nothing but sunlight, atmospheric CO2 and a bit of fertilizer.

Also, by controlling the expression of biological features you could create bioelectronic hybrids that leverage the best of both worlds. Imagine you ship to Mars a few pounds of SoC silicon dies, then grow them into an army of elephant sized drones. They faithfully execute commands with the precision of robots, yet require no maintenance or consumables, living off the land with self-healing capacity.

I believe the idea is not using DNA for general purpose programming as much as controlling biological systems using the paradigms of the software world.

> I believe the idea is not using DNA for general purpose programming as much as controlling biological systems using the paradigms of the software world.

That's not a new idea. I was doing this in grad school. In my postdoc, my boss wanted to rewrite the DNA control structures of our system. I overrode him and told him that the biochemistry needed to be fixed (manipulating the amino acid sequence and not the promoters). On my branch of the track, I got a 16x improvement in yield (we started from trace). On his branch there was no effect.

But what if there was a way to write algorithms that can't be expressed with a von Neumann architecture?

Do you know where I can read about what categories of biocomputation there are? Is there a biological Turing machine that's ever been built, or no, I guess it'd be grown?

As another commenter said, computation is a more vast category than the simplicity of one instruction and then another instruction. Fantastic things can be computed, but most of them are difficult with modern computers.

Parallelization in a biocomputer would also be an important advancement. Like how early computers were room--sized, I can imagine a room full of intricate, strange plants all arriving at their results. That's a lot cheaper too, presumably, then a bunch of GPUs on a rack. Even if it's more expensive, the category of computing it could do might make it still worth it anyways.

Do you think someday that biological computing could perform useful computations?

I'm sure you're busy with important work, you don't have to answer these. I'm sure your knowledge is immense, so your time is precious! Thanks for your comment!

> But what if there was a way to write algorithms that can't be expressed with a von Neumann architecture?

There almost certainly isn’t, due to the universality of computation (see the Church–Turing hypothesis). At any rate, even if this hypothesis turns out to be false (almost unthinkable), DNA won’t offer anything beyond what classical von Neumann architecture offers.

> Do you think someday that biological computing could perform useful computations?

Potentially: proteins are a good potential starting material to build nanomachines. However, this has got nothing to do with this article. As the initial comment said, the article is completely unrelated to biological computing platforms, the title is pure clickbait.

I know it was off the track of the article, I was gravitating to the more interesting idea.

Thanks for your time!

I can't answer you directly but perhaps this helps too.

I recently finished Summa Technologiae from Stanislaw Lem which does investigate a lot of these questions in many of its chapters.

I highly recommend it as it is a detailed, vivid exploration written by a very wise person so much so that it is easy to forget while reading that the book was published more than 50 years ago.

But there's also a practical reason why you might be interested in it even if you wouldn't think anything of a personal(?) recommendation from someone on the internet.

It is based on a lot of academic papers Lem read from all sorts of fields, which are all referenced (at least they were in the version I've read), so it should be easy to then start to look for more recent papers based on those.

I found it online, looks fascinating! Thanks so much!

That's the best kind of book to read, the kind someone wrote after reading a bunch of other books.

http://www.dna.caltech.edu/courses/cs191/

Fellow biochemistry Ph.D. here, and even if you could make this work, good luck finding a usable programming model. This makes quantum computers look easy IMO. And that's too bad because if I worked at Synthego, I could walk to work.

That said, the article seems to be about accelerating genetic engineering rather than a new programming substrate. There's probably 9 to 10 figures in that, no?

The whole article is a fine demonstration of what happens when a Silicon Valley journalist writes a piece on biology without an inkling of what it's all about...

The article is fine. The editor (who provided the title) is the one without a clue.

I remember seeing my first article about biology as a computing substrate when I was a kid and thinking OH MY GOD...and then nothing happened for 100 years. (I am very old.)

Forgive me, but did your message not spring from a biological computing device which is arguably the most marvellous material object to exist in the known universe?

Not exactly human made.

Also I suspect the article is wrong and we'll be outclassed by AI.

Biological AI?

You'll have to convince me that what makes us special is hardware and not software.

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