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I agree with your general premise, that abstraction is essential and sufficient for us to understand a lot of the functions and mechanisms of the cell. I do, h

I agree with your general premise, that abstraction is essential and sufficient for us to understand a lot of the functions and mechanisms of the cell. I do, however, think that the author is right in calling the cell ferociously complex, and that a lot of the abstractions we use hide and gloss over a chaotic system whose particulars can explain a lot of unexplained or misunderstood processes. That's fine to help us get an initial understanding, but you always want to drill down to a lower level abstraction until you (don't) reach the bottom of the stack of turtles. Biology undergoes a major paradigm shift couple of decades, and minor paradigm shifts on an even more regular basis, and I attribute that largely to the increasing resolution with which we're able to observe things. Ten years ago, microscopes were shittier, we were using microarrays instead of RNA/DNA-seq, we weren't using biotinylated-fusion proteins... but that stuff was necessary for us to really prove in a persuasive way ground-breaking shifts like that the DNA->Protein->Function paradigm isn't sufficient to describe a lot of what goes on in a cell. PREEMPTIVE EDIT: I know that DNA->Protein->Function paradigm was questioned way earlier than 2007, but it's taken a lot of persuasive evidence since then using modern techniques to get things like lncRNAs implicated in cancer

RobertoG 10y ago
"a lot of the abstractions we use hide and gloss over a chaotic system whose particulars can explain a lot of unexplained or misunderstood processes." Is not that always the case with abstractions? In fact, is not their point? The article says: "How far is human science from understanding a human brain? [..] Assuming that each neuron contains 175 trillion atoms, the total brain contains roughly 2 * 10^25 atoms." Well, by the same logic, we could argue that we don't understand cars.
- amatic 10y ago
  >Well, by the same logic, we could argue that we don't understand cars Or, by similar logic, that we don't understand how the planets of the solar system interact. It seems that in the history of science, initial views of complex things as chaotic got gradually replaced with better abstractions. As in, the word 'planet' means 'wanderer', then there were epicycles, perfect circles, elipses... I'm not a biologist, but maybe the current abstractions and models of cells are waiting for their Newtons and Mendeleevs to figure out the right models.
  - adrianN 10y ago
    The epicycle theory was actually pretty good and explained planet motion to the precision that measurements of that time provided.
adrianN 10y ago
I agree that better methods of observation tend to yield radical new insights and I'm pretty excited about all the cool things we can do, for example by adding fluorescent markers to biomolecules. But I don't believe that the simplest model that can perfectly explain a behavior of a cell is even in the same ballpark as an atom-scale simulation.

RobertoG 10y ago

"a lot of the abstractions we use hide and gloss over a chaotic system whose particulars can explain a lot of unexplained or misunderstood processes." Is not that always the case with abstractions? In fact, is not their point? The article says: "How far is human science from understanding a human brain? [..] Assuming that each neuron contains 175 trillion atoms, the total brain contains roughly 2 * 10^25 atoms." Well, by the same logic, we could argue that we don't understand cars.

amatic 10y ago
>Well, by the same logic, we could argue that we don't understand cars Or, by similar logic, that we don't understand how the planets of the solar system interact. It seems that in the history of science, initial views of complex things as chaotic got gradually replaced with better abstractions. As in, the word 'planet' means 'wanderer', then there were epicycles, perfect circles, elipses... I'm not a biologist, but maybe the current abstractions and models of cells are waiting for their Newtons and Mendeleevs to figure out the right models.
- adrianN 10y ago
  The epicycle theory was actually pretty good and explained planet motion to the precision that measurements of that time provided.

adrianN 10y ago

I agree that better methods of observation tend to yield radical new insights and I'm pretty excited about all the cool things we can do, for example by adding fluorescent markers to biomolecules. But I don't believe that the simplest model that can perfectly explain a behavior of a cell is even in the same ballpark as an atom-scale simulation.