Wednesday, June 17, 2015

Hopfield on physics and biology

Theoretical physicist John Hopfield, inventor of the Hopfield neural network, on the differences between physics and biology. Hopfield migrated into biology after making important contributions in condensed matter theory. At Caltech, Hopfield co-taught a famous course with Carver Mead and Richard Feynman on the physics of computation.
Two cultures? Experiences at the physics-biology interface

(Phys. Biol. 11 053002 doi:10.1088/1478-3975/11/5/053002)

Abstract: 'I didn't really think of this as moving into biology, but rather as exploring another venue in which to do physics.' John Hopfield provides a personal perspective on working on the border between physical and biological sciences.

... With two parents who were physicists, I grew up with the view that science was about understanding quantitatively how things worked, not about collecting details and categorizing observations. Their view, though not so explicitly stated, was certainly that of Rutherford: 'all science is either physics or stamp collecting.' So, when selecting science as a career, I never considered working in biology and ultimately chose solid state physics research.

... I attended my first biology conference in the summer of 1970 at a small meeting with the world's experts on the hemoglobin molecule. It was held at the Villa Serbelloni in Bellagio, in sumptuous surroundings verging on decadence as I had never seen for physics meetings. One of the senior biochemists took me aside to explain to me why I had no place in biology. As he said, gentlemen did not interpret other gentlemen's data, and preferably worked on different organisms. If you wish to interpret data, you must get your own. Only the experimentalist himself knows which of the data points are reliable, and so only he should interpret them. Moreover, if you insist on interpreting other people's data, they will not publish their best data. Biology is very complicated, and any theory with mathematics is such an oversimplification that it is essentially wrong and thus useless. And so on... On closer examination, this diatribe chiefly describes differences between the physics and biology paradigms (at the time at least) for engaging in science. Physics papers use data points with error bars; biology papers lacked them. Physics was based on the quantitative replication of experiments in different laboratories; biology broadened its fact collecting by devaluing replication. Physics education emphasized being able to look at a physical system and express it in mathematical terms. Mathematical theory had great predictive power in physics, but very little in biology. As a result, mathematics is considered the language of the physics paradigm, a language in which most biologists could remain illiterate. Time has passed, but there is still an enormous difference in the biology and physics paradigms for working in science. Advice? Stick to the physics paradigm, for it brings refreshing attitudes and a different choice of problems to the interface. And have a thick skin. ...
Also by Hopfield: Physics, Computation, and Why Biology Looks so Different and Whatever happened to solid state physics?

See also In search of principles: when biology met physics (Bill Bialek), For the historians and the ladiesAs flies to wanton boys are we to the gods and Prometheus in the basement.


BobSykes said...

My own field was applied biology (wastewater treatment), but Hopfield's comments apply there, too, even today. Analyzing another person's published data is still a no no. And while math (especially bad stats) has invaded biology, it's seldom taken seriously even by those who use it. The biggest problem is that many researchers don't seem to understand that mathematical theories that seem to fit certain data well can make predictions that are absurd about and falsified by other data. That problem is simply ignored.

dxie48 said...

I used to believed in the concept of occam's razor literally. Over time I started to doubt it. The tipping point came when I read about the prediction of the number of DNA base where a physic nobel laureate (could not recall his name) said that based on occam's razor and the number of type of human amino acids there should be 3 DNA bases. As it happened, nature just does what it pleases.

DK said...

Just another of the seemingly endless list of guys who, having not achieved very much of note in biology, blame it on the fact that biology is not physics. His biggest achievement seems to be the "kinetic proofreading" idea. Withholding the fact that it does not involve kinetics, it 1) is a a simple case of coupled reactions equilibrium, 2) is not applicable to the most significant (described later) cases of proofreading in biology, 3) insufficient to explain the experimental data because 4) the actual mechanism turned out to be infinitely more complex (

jeffhsu3 said...

There needs to be 4 because the requirement of Watson-Crick base pairing during replication, you simply can't just have '3' for this. Amino acid encoding isn't everything and is just part of the equation. So no, don't throw Occam's razor out the window.

Cornelius said...

I believe Hopfield used thermodynamic arguments to predict that proteins existed to correct errors in DNA replication. The error rate predicted by thermodynamics was lower than the observed error rate. His prediction was, of course, correct.

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