This matters, for example, if we want to simulate neuronal plasticity or the effect of antidepressants. We're an incredibly long way from a full simulation, which would also require integration with the rest of the nervous system.
To me, this mostly shows that naive beliefs about difficulty aren't really accurate ('but it should it harder to simulate a brain than a cell, because it's bigger right!').
But of course, progress is being made on simulating cells: http://lesswrong.com/lw/drk/paper_simulation_of_a_complete_c... It's a high-level enough model that you can do it with only 1 core per cell.
Also note that: "The model accounts for previously observed gene essentiality with 79% accuracy." This is REALLY bad. Considering they are 'seeding' the model using a biased structure that automatically "knows" that certain genes are essential (for example, they have a 'module' for replication that probably zeroes out if you are missing an important replication component, as opposed to simulating how those genes work at a low level) this is probably somewhere close to as good as flipping a coin.
Yes, you can simulate anything if you abstract away enough. But if the goal is a convincing replication, you'll need to include lots of intracellular effects.
In the end, I believe that practical simulation of a whole brain that you can have a conversation about its existence with is more difficult than the development of quantum computing powerful enough to break all existing crypto.
The work is still interesting, if only because it pushes the limits of what we can do. But I might want to start with an ant brain.
>it is perfectly possible to have a high-level simulation of a 'big' thing which is easier to run than a low-level simulation of a 'small' thing
While this is true, it's not being shown here until we know that this particular high-level simulation actually works. If it doesn't work then it's more of a failed attempt at creating a simulation.
I think an interesting number would be how many atoms does it take to simulate one atom reasonably well. Then you could get correct results for some ( really ) small biological functions.
It's hard to say which is the better approach. On the one hand you have MD from which you could technically build an accurate model "from scratch", folding all of your own proteins as part of the simulation, but it is exceedingly expensive to do that. On the other hand, you have a model built at the level of biochemical reactions and molecular biology, which is computationally feasible, but then you don't have enough information from bench work to flesh it out.
Massive waste of cycles. Never gonna make a useful prediction.
Reduced representations that contain the minimum of complexity to express the phenomena of interest are far more useful.
I'm no molecular biologist, so i'll happily agree if you say there are some fraction of water molecules broken down, or formed by various cellular processes, but that must be a tiny fraction of the total, and could just be special cased.
It just seems like you're willfully ignoring everything physics has to say about how the universe works so you can get a big number for your calculation.
That's not to say that you can't get useful results by treating solvent as a continuum (or even ignoring it entirely), they'll just have a different kind of explanatory power.
[1] http://www.sciencedaily.com/releases/2013/07/130728134055.ht...
My understanding of "solution" is stuff floating in water. If there's some value in breaking out each atom, i'm all for it, but i kind of suspect the spherical cow is good enough in that case.
Even if i'm wrong there, each atom would introduce at least 6 degrees of freedom. IIRC, water is slightly polarized, and that's likely relevant to at least some reactions. Replacing the 18 degrees of freedom with 6 to represent a rigid water, or perhaps 10 or so to represent a flexible version, modeling as the molecule will dramatically lower complexity.
http://mgl.scripps.edu/people/goodsell/illustration/mycoplas...
I don't understand why it's easier to simulate each individual atom than it is to simulate things with structure. I would assume a simulation would regard the long yellow strands of dna as dna rather than the component parts.
I'm used to a world where having structure implies constraints. With constraints, simulation can avoid a bunch of special cases and is therefore faster. I find foobarbazqux's approach of simulating each atom upsetting. But that's ok. You guys seem to think it's the way to go, and you all get results. shrug
-edit-
I don't think simulating water is easy, but i believe it's likely easier to simulate water than it is to simulate all possible states of the constituant atoms.
In that case, don't even bother with trying to work out what it would take to mathematically model biochemistry yet. Go study some basic physics and chemistry for a few years instead.
I am not attempting to be insulting, I am attempting to point out to you that you need to go and learn a hell of a lot more about the sciences than you seem to know at the moment if you are going to have any sort of productive discussion about the technical aspects of modelling biochemistry.