Comment by mnemonicsloth | Hacker News Reader

Comment by mnemonicsloth | Hacker News Reader

Metagenomics is the biological equivalent of suddenly being able to see dark matter.

Normally, if you want to analyze a microbe, you do it by culturing the organism in Petri dishes. By varying the growth medium you can find out a lot about your organism: what it eats, if it breathes, how it metabolizes various things. The problem is that only 5-10% of bacteria grow on plates. Microbiologists call this the "plate count anomaly" and what it means is this: your sample in a microscope could be teeming with life, but if you plate it you'll probably get this homogeneous little sample of not very many organisms. The rest are called "microbial dark matter."

With metagenomics, we could see them all. It made people a little funny in the head. You might remember that "The Microbiome" was a big idea in the media for a while. It got pretty flattering treatment, considering what it is: a mass of mostly proto-shit floating around inside your colon. But the enthusiasm wasn't too far misplaced, because a major area of biology is growing by leaps and bounds now.

If you are a computer programmer considering a career change you should really take a day off to look into the new genetic technologies on offer. Performance is doubling every year [1]. The world is changing. And computing is at the center of it, both practically (all that research generates a lot of data) and conceptually (because gene expression is information processing). So give it a look.

[1] Remember that? https://en.wikipedia.org/wiki/Moore%27s_law

>If you are a computer programmer considering a career change you should really take a day off to look into the new genetic technologies on offer.

What resources would you recommend, and do you have any advice for someone who is just starting their career?

Yeah, not that I’m looking to make any moves but I’d love to do some reading.

It depends on how big a commitment you want to make. I quit my job to go study biology and it worked out pretty well for me. Programming opens doors for you because the majority of biology grad students can't do it. You get good work and an accelerated path through classes, TAships, research and other university business. If you want to work in IT, the experience you get is perfect for applying for prestige places like Google, Facebook or Amazon. Mostly I've spent the last year writing pattern matchers to extract subtle patterns from huge data files.

If you're not ready for a big commitment (and even if you are), I'd recommend taking some classes too get a feel for the subject. Khan Academy has two (or you can google around for more) that look pretty good. The just-plain-Biology one covers a surprising amount of useful information. The one on Genetics is useful too, although you might want to skip past some of the stuff about cross-breeding animals and whatnot.

Another thing you can look at is Synthetic Biology, which is biology plus design, biology for hackers. Synbio says biology has been too interested in describing and cataloguing, and not interested enough in building. So even though what we can do is pathetically simple next to the evolutionary process that designs new organisms, we can still do little things like making human beings immune to all viruses and designing cyanobacteria that produce crude oil from air, water and sunlight. If you're interested in Synbio you should check out the iGEM competition, which is a major event and an organizing site for useful information.

If you don't feel like crawling around the iGEM database of standardized biological parts (it's like the library docs for Life) you could look at these videos instead: https://www.ibiology.org/playlists/synthetic-biology/

Email's in my profile. Don't be a stranger if you have questions.

Though I'm still very early into it, I can highly recommend starting a biochemistry degree, if you already have a programming/computer science background. Bioinformatics would be the direct route to that field, but in a bioinformatics degree, there is usually still not much of a focus on the low-level biochemical mechanisms and biochemical methods that form the basis for all the data you will be working with. Biggest downside though is a lot of lab-time, which for me personally is hard as I'm still freelancing on the side.

I'm only in the middle of my second semester and through taking a few biochemistry classes in advance and reading though the papers of our universities research groups it's already starting to come together a bit. Things start to click and I'm getting pretty far in trying to understand and reproducing some SOTA papers in weekend projects. For such a short amount of time of studying the subject, I think that's a pretty good payoff.

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