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Biology Will Be the Next Great Computing Platform

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Re: Biology Will Be the Next Great Computing Platform

#61
post #37
post #9

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 computat…

"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…

>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."

Re: Biology Will Be the Next Great Computing Platform

#62
post #17
post #9

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 computat…

> 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.

Re: Biology Will Be the Next Great Computing Platform

#63

Earlier quoted context omitted.

Life doesn't solve "problems" though - it just creates random order from chaos. What kind of problems do you even have in mind? What would you even solve if we could somehow understand or control these bigger forces of organization? I agree with the OP, we are not replacing silicon with DNA or anything - this article is just another "tech" article that shouldn't exist.

> Life doesn't solve "problems" though Wait, what? Biological systems are not solving problems? It does so all the time! Seriously? > it just creates random order from chaos. You get that with just physics, on a large scale for example the formation of galaxies and stars, or when things self-sort by weight in a gravity field (heavy stuff goes to bottom of a solution, lighter stuff goes to the top).

I think he ment life in a broader perspective (i.e. evolution) not conscious and aware biological systems as in humans.

I would argue that very few biological systems solve problems, what they do is serve a function which has been dictated by evolution.

But at no point is there any purposeful act of solving problems just like your genes aren't selfish they just behave as if they are.

Re: Biology Will Be the Next Great Computing Platform

#64
post #45

Earlier quoted context omitted.

> No it is not. Analog computers were used before good digital computers could be produced, for the same roles and straightforward problems. Actually, analogue computing was still widely used for simulation and the like in many industries well into the 70s and 80s. Though often augmented with digital computers, for various purposes (simulation series, automated recording/reporting etc.)

I think "70s and 80s" is well within the definition of "before good digital computers could be produced" in the context of many industries. You guys aren't disagreeing.

16 bit minis were, well, not common, but still used in numbers in labs and the like. Consider that d. computers are mostly used for information systems nowadays, meanwhile analogue computers were not used at all for that purpose. So apart some inventive examples I won't rule out, no company migrated from paper to analogue computing to digital computing, because analogue computers were not suited for information systems.

That's likely why analogue computers persisted for fairly long after the introduction of digital computers: they solve very different problems, and an analogue computer could solve simulation problems at a speed that the 16 bit mini right next to it would never achieve. Also, they are highly modular (in fact they are nothing but a bunch of fundamental modules like integrators, diffs and other filters that the user interconnected as required) and very easy to extend with specialized circuitry and the like. Thus, from a purchase/investment point of view, analogue computers could easily be scaled, while this was more difficult with digital computers.

Re: Biology Will Be the Next Great Computing Platform

#65
post #9

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 computat…

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?

Re: Biology Will Be the Next Great Computing Platform

#66
This article reads like a PR press release. You can't talk about biocomputers in 2018 without mentioning Tom Knight[1] and iGEM[2]. Knight not only pioneered this "next great computing platform," he also pioneered the current one: Knight was involved in early ARPANET work, Lisp Machines (MIT was the second organization after PARC to build networked personal workstations), and massively parallel SIMD (ie GPU) work on the Connection Machine.

[1] http://people.csail.mit.edu/tk/ [2] http://igem.org/Main_Page

Re: Biology Will Be the Next Great Computing Platform

#67

Occasionally I see posts, for example on reddit but also discussions here, about what other programming languages a programmer could learn as the next (and higher) step in ones ongoing education. My suggestion for what to do after the CS degree, a road I took myself during the last few years, is to go to edX (or Khan Academy for any missing basics) and at the very least take MITs "Introduction to Biology", which actu…

Would you mind talking about what field or area you work in?

I came from a bioengineering background and ended up doing a lot of computational work (signals and communication systems, ML, FEA), so I feel like we are arriving at the same conclusion from opposite sides.

Re: Biology Will Be the Next Great Computing Platform

#68
post #37

Earlier quoted context omitted.

"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…

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 cell…

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...

Re: Biology Will Be the Next Great Computing Platform

#69
post #67

Occasionally I see posts, for example on reddit but also discussions here, about what other programming languages a programmer could learn as the next (and higher) step in ones ongoing education. My suggestion for what to do after the CS degree, a road I took myself during the last few years, is to go to edX (or Khan Academy for any missing basics) and at the very least take MITs "Introduction to Biology", which actu…

Would you mind talking about what field or area you work in? I came from a bioengineering background and ended up doing a lot of computational work (signals and communication systems, ML, FEA), so I feel like we are arriving at the same conclusion from opposite sides.

I studied CS, worked as a consultant and at a major Linux company, later as a freelancer. Learning stuff feels good :-) Even better when it's something I never ever expected to learn, since I thought that after choosing my field of study for university my path was all set. Thanks Internet - possibilities truly have increased by orders of magnitude compared to my youth!

Re: Biology Will Be the Next Great Computing Platform

#70
post #18

Occasionally I see posts, for example on reddit but also discussions here, about what other programming languages a programmer could learn as the next (and higher) step in ones ongoing education. My suggestion for what to do after the CS degree, a road I took myself during the last few years, is to go to edX (or Khan Academy for any missing basics) and at the very least take MITs "Introduction to Biology", which actu…

IMHO these courses only scratch the surface, good to learn a thing or two, without much applicability. I am right now searching for a degree path in Biochemistry or Molecular Biology online. I want to spend time on it, but be able to actually apply my knowledge. There are so few of them (maybe because of the lab classes, idk). I've found online degrees in ASU ( https://asuonline.asu.edu/online-degree-programs/undergr…

> IMHO these courses only scratch the surface

Of course - that is what I recommend to programmers and CS majors, working in those jobs, on the side, not as a career path.

But in any case, those are "real" courses, so "scratching the surface" not because they are dumbed down but because those are the freshman courses. Of course year 2+ students will get more advanced courses not usually found on edX (although they have quite advanced topics in physics, for example https://www.edx.org/course/mastering-quantum-mechanics-part-...).

As I said, an alternative to learning yet another only mildly different programming language (that runs on the exact same pieces of silicon as the other ones they already know, so it cannot be fundamentally different by definition).

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