I think of this Richard Feynman story pretty often.

Apparently Feynman spent a short episode of his career dabbling in biology. This story recounts his experience taking a graduate level biology course. The professor has assigned him to present a paper to the class:

“I began to read the paper. It kept talking about extensors and flexors, the gastrocnemius muscle, and so on. This and that muscle were named, but I hadn’t the foggiest idea of where they were located in relation to the nerves or to the cat. So I went to the librarian in the biology section and asked her if she could find me a map of the cat.

“‘A map of the cat, sir?’ she asked, horrified. ‘You mean a zoological chart!’ From then on there were rumors about some dumb biology graduate student who was looking for a ‘map of the cat.’

“When it came time for me to give my talk on the subject, I started off by drawing an outline of the cat and began to name the various muscles.

“The other students in the class interrupt me: ‘We know all that!’

“‘Oh,’ I say, ‘you do? Then no wonder I can catch up with you so fast after you’ve had four years of biology.’ They had wasted all their time memorizing stuff like that, when it could be looked up in fifteen minutes.”

—Richard Feynman (Surely You’re Joking, Mr. Feynman!)

This story resonates with me as a computer scientist/mathematician working on biological problems.

I’ve found that physicists (and computer scientists) have very different sensibilities from biologists. I think Ernest Rutherford had these differences in mind when he said “All science is either physics or stamp collecting.”

Biologists are required to memorize a great many facts. In contrast, computer scientists, mathematicians, and physicists only memorize a small number of “first principles”. Those principles serve as a starting point to reason/solve problems/understand the world—you can get a lot of mileage out of a small number of good abstractions.

Meanwhile, biological systems are like Rube Goldberg machines. Very little of biology can be explained from anything resembling “first principles.” The central dogma is the closest thing to a first principle I can think of, but it explains only a small fraction of the mechanisms people find interesting.

A competent biologist must (a) learn a large number of facts and (b) form a unified understanding from them. I feel optimistic that algorithms, ML, and AI can do a good job of this. I’m not very interested in stamp collecting—but I am very keen to develop algorithms that collect stamps for me.

Whenever I feel my computer scientist mindset collide with the stamp-collecting aspects of biology, I think of it as a “map of the cat” moment. I only wish more people knew this Feynman story, so that I could say “map of the cat” out loud and people would understand what I mean.

\( \blacksquare\)