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Comment by achenatx | Hacker News Reader

Finally :) I have a degree in electrical engineering and a degree in immunology (in the early 90s) and was 100% sure that control systems math should be applied to biological systems, like the immune system.

Most biologists tend to take very little math (calculus and stats) and dont even realize that control systems are a thing.

We definitely need more of that cross pollination.

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Biology is a lot cooler to the geek crowd when you reframe it as the study of (natural) self-replicators.

Or as the only existing example of working nanotechnology. This realization was what made me interested in life sciences. Before, biology in my mind was mostly cataloging various peculiarities of animals and plants, which I found utterly boring. I think the switch flipped when I stopped looking at life sciences as studying an art piece, and started looking at it as reverse engineering of an incredibly complex family of machines, with full intent of using gained knowledge for practical purposes.

If by "control systems" you mean Cybernetics, then this is even more late. Remember "Bionics"?

edit: D'oh! I commented before reading the article. Sorry. It does mention Cybernetics.

Control systems are not cybernetics. They are mathematical models. You can look it up.

To be fair cybernetics is directly name checked in the article though: “Norbert Wiener proposed that regulatory systems in both animals and machines should be studied together, in a field he named cybernetics”

Cybernetics is the original "control systems math", which was then forgotten/ignored in the West (the Soviets messed with it some I think) and re-invented as "Control Theory" by people trying to control factories and such.

As the article states, Cybernetics as originally conceived makes no distinctions about the physical (or otherwise) nature of the underlying processes it models, and it was explicitly expected to unify the math of feedback and control in biological as well and mechanical systems.

The fictional "Bionic Man", et. al., was an exploration in the popular imagination of how this might result in e.g. artificial limbs and organs that worked like the real thing and, in the stories at least, even improved on them.

In any event, what this article describes could be called cellular bionics.

greybeard spotted :P

Nit pick - The "original control systems math" is Bode, Black, Nyquist.. 1930's. Cybernetics is the application of control theory (branch of mathematics) to biology; Norbert Wiener, Ashby, etc, 1950's.

Nit pick to a nit pick: from what I can gather from the title of Wiener's book[0], it was never about biology. It was just about applications of control theory to physical mechanisms, be it biological or man-made.

[0] - https://en.wikipedia.org/wiki/Cybernetics:_Or_Control_and_Co...

Looks like wikipedia is the source of confusion in this case. "The book laid the theoretical foundation for servomechanisms (whether electrical, mechanical or hydraulic), automatic navigation, analog computing .."

Servomechanisms existed way earlier than 1948, so did analog computers - navy ships in WWII extensively used both in gun control, to move the guns and calculate balistic trajectories, etc. Wiener merely wrote down existing knowledge, and suggested it could also be applied to humans.

> navy ships in WWII extensively used both in gun control, to move the guns and calculate balistic trajectories, etc.

> Wiener merely wrote down existing knowledge, and suggested it could also be applied to humans.

A little more than that.

> During World War II, his work on the automatic aiming and firing of anti-aircraft guns caused Wiener to investigate information theory independently of Claude Shannon and to invent the Wiener filter.

https://en.wikipedia.org/wiki/Norbert_Wiener#During_and_afte...

But you're absolutely right that "original control systems math" is older than cybernetics, well met.

> Most biologists tend to take very little math

Wow, really? That's surprising to me. The hardest course I ever took was one I took for my MSCS in bioinformatics. It seemed very math-heavy, and math-heavy in ways that I couldn't lean on my past experience to "muscle" my way through.

In my experience, a lot of biologists learning bioinformatics/genomics tend to learn a specific set of general tools (HMMs, multiple hypothesis testing, PCA, etc.) and then learn some specific statistical tools that apply to their data (e.g negative binomial GLMs for RNAseq).

There is enormous room for original, fundamental, groundbreaking work here.

Both you and the OP are right in your own ways. It's worth remembering that bioinformatics, computational biology and other inter-disciplinary fields like these (mathematical oncology comes to mind) are relatively new and the proportion of biological sciences graduates doing these are dwarfed by the number that go through a "conventional" (as probably alluded to by the OP) biological sciences curriculum. Mathematical modeling in biological sciences is incredibly hard because of the sheer complexity in the many layers that comprise our knowledge of biology (cell layer. molecular biology layer, tissue layer etc) and I generally agree with the sentiment that more investments in research at the math-biology intersection will further our ability to understand biology better.

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