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Comment by Lambdanaut | Hacker News Reader

This project is huge. I'm glad to see it has come this far. It's the first ever simulation of a multi-cellular organism at a really useful detail, presented and made available to the masses.

It's work like this that is going to help explode the use of citizen scientist work. Imagine being able to run your own experiments on a simulation first without having to buy and breed your own worms. So many more experiments can be carried out, and in parallel too.

It's not an exact model yet, but it's getting closer. The end goal is to get the model to the point where if you run an experiment on the virtual worm, you can be certain you'll get the same results on the real worm.

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I completely agree, while at the same time I wonder if they're not being too ambitious--are there simulations like this but for simpler organisms, preferably that is open source as well? I would love to be able to just inspect and toy around with a cell and its organelles, protein production, etc, in a visual as well as programmatic way. I think that's what's missing (as in I haven't come across it) in getting me into "diy biology" as a hobbyist.

There's this project by Stanford to simulate Mycoplasma genitalium: http://wholecellviz.stanford.edu

There's also this, which is part of the project above: http://www.cell.com/abstract/S0092-8674(12)00776-3

The problem is you need to know about tons of stuff before doing anything useful with it. For example, you need to know the biology of M. genitalium (or even what the hell it is) and you need to know at least a little bit about how the biology works (i.e. what is the metabolome? etc.). Then you need to know enough about software to be able to install and get everything running (often with poor documentation). Sometimes you need access to expensive software like Matlab.

So I guess that means it's coming, but very slowly and only for people who are in the field, not DIY biologists.

This is actually something I'm interested in working in (once I get to grad school).

I'm sorry, but this sounds like a fantasy land. I am extremely skeptical that you could get a detailed and accurate enough simulation to reveal any useful novel results.

The list of "unknown unknowns" that we don't even know about, yet alone are able to attempt to simulate, is impossibly large.

This reminds me of the old Star Trek episodes where they would simulate the effect of the new-fangled quantum-slipstream-tachion-whatever-warp-drives in their Holodeck and then obtain meaningful results.

Of course, that was nonsensical fiction. I don't see how this could be different.

Simulations and models need to be incredibly focused. The art of modeling is figuring out what to exclude from the model, not what to include. Any attempt to make a really general purpose model/simulation is almost bound to overreach and fail.

This is the mindset that has prevented people from even attempting such projects, it is poisonous and anti-intellectual.

One thing that we almost NEVER do is with models is force them to interact with each other. This means that we are completely blind to an entire aspect of isolated models: namely that inputs may not have the structure we expect, or that their outputs don't actually have the anticipated affect on downstream models. Most current model validation is purely speculative or based only on a finite dataset. If you take two models that you think effectively represent how the world works and put them together and suddenly they no longer work, then you reveal a huge gap in our knowledge. In a sense this is the ultimate form of model validation and until you do it any interpretation you make about how models might or might not work together is complete bullshit.

I spend a lot of time working on models. This is not a "poisonous and anti-intellectual" statement, it is simple a statement grounded in experience.

There are dozens of failed projects to make different models work together. It would be such a beautiful concept if we could "snap" different models people built together like legos and watch how they interact and develop together. It is also a concept very inline with the hacker mindset where we all observe the phenomenal success of the UNIX building block approach to getting things done.

It is a great idea in theory, but in practice making models work together is incredibly difficulty. You have massive issues of scale (specifically in regards to temporal scale with process going on at very different rates) and context. This has been tried again and again. There are many software packages designed to make this easy. As a general rule, they simply do not work outside of narrowly focused domains.

What is "poisonous" to science (and science funding) is to overpromise and underdeliver. What is also "poisonous" is to ignore a long history of modeling and simulation work and the hard-earned lessons and failures gained from that work.

The only reason I say that mindset is problematic is because the way you frame your statement is "this can't be done" when what is actually the case is that we have never really tried because there are many other easier problems to solve. I don't think anyone who has spent even a limited amount of time modelling expects to be able to stick a few equations together and have it all work. It is still an open question as to whether we can capture say 95% of the variance in a system using a collection of simplified models or whether we have to go full monte carlo and study models that have the full complexity of the system they represent because you really do need every last single part and can't simplify anything.

There will be novel results no matter what happens, maybe not about c elegans, but certainly about the models themselves.

This model is definitely excluding a lot of details. For instance, the cells are modeled on an abstract functional basis. There isn't any cellular division occuring and it's going to take a lot more work to ever get to that level.

For purely simulating behavior and understanding how the insides of the worm "function together", this model is a fantastic breakthrough.

I perhaps was being hyperbolic with my original description of the worm being a catch-all for any experimentation whatsoever, but you have to admit that it has vast implications.

(You also don't deserve the downvote you got. We always need somebody anchoring us to reality. )

Outside of the germline, C. elegans does not undergo cellular division in the adult stage. There is a fixed developmental pattern, with exactly 959 cells in the adult hermaphrodite. Also, the connectivity map of the entire nervous system is known.

Thanks for clearing that up!

I do believe that this is a permanent showstopper for modeling C. Elegans reproduction, correct?

I would be very curious to hear if there have been any plans to one day re-visit the model to allow reproduction, and if any thought has gone into how that process could be allowed!

> Imagine being able to run your own experiments on a simulation first without having to buy and breed your own worms. So many more experiments can be carried out, and in parallel too.

I'm trying to better understand the significance of the project. Can you explain this more? Wouldn't running experiments require similar level detail simulators for whatever you are trying to test?

Usually when you do a genetic experiment, you have a model of how things work in your head, then you do the experiment and test that model on living organisms.

It's entirely possible that your model is way off and you get results that don't mean anything. With computational models, we can test hypotheses (the models in our heads) much faster (don't have to wait for the worms to grow up) and much cheaper (we can do it on the computers all of us already own).

Gotcha, makes sense. Very cool, thanks.

Is it fair to say that such project would have difficulty raising funds from traditional academic sources like NSF?

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