Will we ever be able to simulate a living cell? In theory. Molecules collide, proteins fold, and all of these things can be modeled on a computer. But there are so many unknowns, and so much compute would be required, that a mechanistic model of the cell remains a... distant dream. Still, many research groups are trying to build cells "from the bottom up," mostly by stringing together mathematical equations that represent different parts of the cell. By *trying* to build an accurate model of the cell, they hope to improve our own understanding of how biology works. In doing so, they also maintain legibility, meaning that humans can understand and interpret all the equations used to construct the model. But Adam Green argues that legibility is a constraint on our models. He thinks that "human legibility, our ability to understand a system...has been limiting us." To truly accelerate biomedical progress, Green thinks that we should discard assumptions about legibility in favor of "more black box" models. Neural networks can make sense of biological data in a way that hard-coded equations cannot. This is not a new argument. A 2019 essay by Bert Hubert, called "Is biology too complex to ever understand?" makes much the same point. In that essay, Hubert writes: "There is no rule that says nature cannot be more complex than our brains can handle." Instead of trying to make sense of biology via reductionist observations and mechanisms, Hubert argues that we should just gather everything into databases "that might enable computers to make sense of what we have learned." (This vision is now playing out in many research groups.) This "black box" approach might be useful (in terms of modeling cells to cure diseases, say) but would be unsatisfying in the sense that it doesn't deepen our own understanding of the universe. And isn't that a key part of science? Is science for humans -- an act that satisfies some itch -- or rather a means to an end? I think both approaches are useful. The black box models may help us cure diseases faster by making useful predictions that our brains cannot (currently) comprehend, but the mechanistic models deepen our own understanding of how cells work.show more

Niko McCarty.

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