3 ms·

The only time I’ve seen this happen is AlphaFold. Every other time some math or software guy came into biology it worked exactly like in xkcd.

anonymouskimmer 4y ago
That's a good one.
deltree7 4y ago
The biggest innovation of this decade, LLMs was created by Math/CS not linguistics
jltsiren 4y ago
Biology has already been transformed by mathematics, statistics, and CS for decades. These days, if something like in that xkcd happens, those people are probably not even familiar with the relevant parts of math / stats / CS.
- ramraj07 4y ago
  What exactly has it transformed? Nothing has fundamentally changed in biology, you still have to run western blots and give mice cancer. A great example of “math” solving biology is super resolution - which was just a dud.
  - jltsiren 4y ago
    Genomics, for example. The entire field could not exist without extensive algorithmic research done over several decades. Even today, many of the key people in the field have a background in CS and mathematics. Theoretical ecology is a bit more old-school answer. Many mathematicians have been involved in that field.
    - ramraj07 4y ago
      I am not sure I have seen any meaningfully brilliant breakthroughs in those fields though. I take that back. One can never forget the brilliance of HiC by Erez. But other than that TBH all other “mathematical” or computational breakthroughs I’ve seen are just at best meticulous application of obvious math and computational algorithms to biological problems (and may I say poorly? Thinking back to the microarray nightmare years).
      - jltsiren 4y ago
        I guess that depends on what you count as a breakthrough. From my perspective, HiC is a small detail, and even AlphaFold is just the latest improvement to an existing process. A true breakthrough would be something like ancient DNA, which gave the humanity a new tool for studying the past. Pretty much everything in genomics depends on shotgun sequencing, which in turn depends on CS. The algorithms used for assembling something useful out of the sequence reads are highly non-obvious. In fact, most developments in string algorithms since the 80s have been driven by the needs of DNA sequencing. (Information retrieval used to be another contender, but word tokens turned out to be a better tool for that field.)

anonymouskimmer 4y ago

That's a good one.

deltree7 4y ago

The biggest innovation of this decade, LLMs was created by Math/CS not linguistics

jltsiren 4y ago

Biology has already been transformed by mathematics, statistics, and CS for decades. These days, if something like in that xkcd happens, those people are probably not even familiar with the relevant parts of math / stats / CS.

ramraj07 4y ago
What exactly has it transformed? Nothing has fundamentally changed in biology, you still have to run western blots and give mice cancer. A great example of “math” solving biology is super resolution - which was just a dud.
- jltsiren 4y ago
  Genomics, for example. The entire field could not exist without extensive algorithmic research done over several decades. Even today, many of the key people in the field have a background in CS and mathematics. Theoretical ecology is a bit more old-school answer. Many mathematicians have been involved in that field.
  - ramraj07 4y ago
    I am not sure I have seen any meaningfully brilliant breakthroughs in those fields though. I take that back. One can never forget the brilliance of HiC by Erez. But other than that TBH all other “mathematical” or computational breakthroughs I’ve seen are just at best meticulous application of obvious math and computational algorithms to biological problems (and may I say poorly? Thinking back to the microarray nightmare years).
    - jltsiren 4y ago
      I guess that depends on what you count as a breakthrough. From my perspective, HiC is a small detail, and even AlphaFold is just the latest improvement to an existing process. A true breakthrough would be something like ancient DNA, which gave the humanity a new tool for studying the past. Pretty much everything in genomics depends on shotgun sequencing, which in turn depends on CS. The algorithms used for assembling something useful out of the sequence reads are highly non-obvious. In fact, most developments in string algorithms since the 80s have been driven by the needs of DNA sequencing. (Information retrieval used to be another contender, but word tokens turned out to be a better tool for that field.)