God. Thank you for this. As an incipient biomedical researcher with still 2 years to finish training, I feel like every time I google or pubmed my subject matter of interest I'm being scooped. Just yesterday I was quite mad as a company looking to solve the problem I am working on opened with a bunch of researchers from other institutions. I felt like I was late once again.
The final paragraphs make me think of David Epstein's Range, and how training or even basic understanding of methodologies outside one's area open conceptual frames to better tackle questions.
I occasionally have the same feelings. Like it seems like people have basically figured out everything in biology. Most papers are written with that kind of authoritative tone, which is understandable given the pressure of the publishing process.
So occasionally I have to remind myself that 600k people a year die from cancer, which is what I’m studying. It’s quite dark but it’s also the truth. We have absolutely no idea how biology works. There is so much left to understand.
Also if you feel like you’re being scooped by already published papers, that is good. You’re having the same ideas that researchers had just a few years before. You’ll find the gaps eventually.
The funny thing is, for my entire (scientific) career, I never felt like anybody was scooping me. Instead, I felt like I was waiting for the rest of the literature to catch up with where I was mentally, years before. Many of the things that I worked on as an undergraduate sort of... didn't go anywhere for 20-30 years until neural nets became awesome again.
This paper inspired another fun followup: "Could a Neuroscientist Understand a Microprocessor?" [0] The authors investigated a 6502 running Atari games using popular neuroscience methods, finding things like transistors that are uniquely necessary to run Space Invaders, but, of course, never getting close to an actual understanding of how the processor functions. It really highlights how even with the huge amounts of data we are able to get from biological systems now, there's still a lot of information we paradigmatically can't understand.
But... clearly in the case of Space Invaders, we can understand it as we built it. The lesson I would think you should learn from that argument path is that techniques and mental models matter, and that the "popular neuroscience methods" should be re-analyzed and potentially discarded outright.
I can imagine a whole series of quite amusing articles of that form, but it would probably not be a good idea to take it too far. When it got to "Could a Particle Physicist Understand Birds?" and ended up with the physicist building and using a Large Heron Collider people would probably get rather upset.
for the record, neither geneticists, molecular biologists, nor biochemists, have the techniques to reverse engineer biology at the holistic level. That task was left to the biophysicists who combined a collection of techniques to uncover the inner workings of a wide range of biological processes (ribosome, motor proteins, neuron function, the structural basis of DNA replication...)
I liked the article. One thing that I think was missed is that the engineers can understand the circuit because they designed it. We know what the capacitor symbol represents because we designed a circuit that only depends critically on a small number of parameters represented by that symbol (and maybe an accompanying bill of materials). We chose design elements that are, themselves, understandable as a language, and laid out the diagram with a prior knowledge of what ideas we were trying to convey.
Having had to do so, coming up with the schematic by inspecting the circuit is much more difficult.
[The joke is that biologists will describe incredibly complex units in a complex system by just labeling it a -tome, which obscures the underlying complexity. Not intentionally, that’s just the limit of our knowledge].
The "circuit diagram" of a biological process, complete with quantitative parameters, is known as a "kinetic model," and I think these are slowly growing in popularity.
Quantitative reaction kinetic constants are quite hard to obtain, hence the qualitative "A raises B and lowers C, B raises D, C raises D" mess where even that simple sentence I told you gives you nothing about the relationship between A and D.
I don't think anyone looks at a process diagram with zero known constants and says "that's the way that things should be," but at the same time, it's so difficult to tell what those constants are that the uselessly unconstrained diagrams are still, oftentimes, the best that can be done.
An analog radio is probably the best case scenario for lesion study. The main purpose of the radio is signal processing, which is done in serial with not many inter-communicating parts.
In fact I think it should be possible for biologists to repair a radio. The main discovery these biologists have to make is that the signal is encoded in electrical voltage, they would then be able to measure the input/output voltage of each discrete component and come to an understanding of the signal processing pipeline. I had an undergrad electronic design course that was exactly this.
A digital radio would be much harder, since the signal processing is done in software.
In some ways the author was already behind the times. As recently as 1995 there were graduate students in Houston repurposing circuit simulation software to study biochemical pathways. I imagine in the intervening quarter century more tailored techniques and mechanisms have been developed.
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[ 3.5 ms ] story [ 49.8 ms ] threadThe final paragraphs make me think of David Epstein's Range, and how training or even basic understanding of methodologies outside one's area open conceptual frames to better tackle questions.
So occasionally I have to remind myself that 600k people a year die from cancer, which is what I’m studying. It’s quite dark but it’s also the truth. We have absolutely no idea how biology works. There is so much left to understand.
Also if you feel like you’re being scooped by already published papers, that is good. You’re having the same ideas that researchers had just a few years before. You’ll find the gaps eventually.
There will be fewer gaps, and they will be smaller, thus harder to find.
[0]: https://journals.plos.org/ploscompbiol/article?id=10.1371/jo...
"paradigmatically can't understand" = "can't figure out using current methods", so pretty much what you're saying
for the record, neither geneticists, molecular biologists, nor biochemists, have the techniques to reverse engineer biology at the holistic level. That task was left to the biophysicists who combined a collection of techniques to uncover the inner workings of a wide range of biological processes (ribosome, motor proteins, neuron function, the structural basis of DNA replication...)
I would be remiss in failing to mention https://en.wikipedia.org/wiki/There%27s_Plenty_of_Room_at_th... and https://en.wikipedia.org/wiki/What_Is_Life%3F which inspired me to a career of nanomedicine.
Having had to do so, coming up with the schematic by inspecting the circuit is much more difficult.
If I remember correctly, all you need to fly an airplane is a pilotome, an enginetome, and a aircraftome. Inhibitors are bird strikes and weather.
Easy right?
Found Derek Lowe’s commentary on it: https://www.science.org/content/blog-post/flightosome
[The joke is that biologists will describe incredibly complex units in a complex system by just labeling it a -tome, which obscures the underlying complexity. Not intentionally, that’s just the limit of our knowledge].
Quantitative reaction kinetic constants are quite hard to obtain, hence the qualitative "A raises B and lowers C, B raises D, C raises D" mess where even that simple sentence I told you gives you nothing about the relationship between A and D.
I don't think anyone looks at a process diagram with zero known constants and says "that's the way that things should be," but at the same time, it's so difficult to tell what those constants are that the uselessly unconstrained diagrams are still, oftentimes, the best that can be done.
In fact I think it should be possible for biologists to repair a radio. The main discovery these biologists have to make is that the signal is encoded in electrical voltage, they would then be able to measure the input/output voltage of each discrete component and come to an understanding of the signal processing pipeline. I had an undergrad electronic design course that was exactly this.
A digital radio would be much harder, since the signal processing is done in software.