Wednesday, April 13, 2005

We hateses the nasty, smelly Systems Biologies

Here's a quote from a paper that we're reading for my cell biology class

"In an age when a great deal of cant has been written about the coming of age of systems biology, the experiment from Musacchio's lab reveal the variety of experiments that are essential to understand complex biological control mechanisms in this day and age. Structural biology, genetics, hardcore biochemistry and sophisticated imaging of tagged proteins in vivo are all required simply to begin to think clearly about sophisticated biological processes, and highly sophisticated experiments are required before one can begin to contemplate the utility of mathematical modeling. Future departments of systems biology might take note."

I found this particularly interesting because I'm in the brand-spanking-new [just started this year] Computational and Systems Biology PhD program, so it's educational to hear what people think of "systems biology", a term that has come into vogue relatively recently. I've also wondered what "traditional" wet lab biologists think of the general push to introduce lots of computation and mathematics into biology and all the noise being made about the future of biology being in computation. Even if you apply an appropriate discount factor to take into account the usual overly optimistic predictions that "the future of X is Y", all that talk has to be somewhat disconcerting if computation is something you have little/no background in, especially given the need to constantly be on the cutting edge of science.

Based on the quote above, Kim Nasmyth's opinion of systems biology and computational modeling seems to be rather low. On one hand, I agree with him that, in the end, you're going to have to confirm your mathematical models with experimental support [and have said so, towards the end of this post] and so you shouldn't be too gung-ho about these models. On the other hand, I do think that making the blanket statement that [all] mathematical models are currently useless is throwing the baby out with the bathwater.

I think the utility of a model depends on what you want to do with it. His take on mathematical models seems to be that they're all intended to either be based on or give deep insight into what's happening at a mechanical, molecular level, and that if they can't do that, they're useless. That seems to miss the point of many models, which is to give you an idea of the sorts of things you should observe at a high level if the system works the way you think, allow you to easily experiment with different possible system organizations and just try to get a feel for what might be happening in the system. For example,
if all you want to do is built a model that will tell you what will happen if you press on a car's accelerator, you don't need to know things like the volume of the cylinders, what metal they're made of, what the length of the crankshaft is etc., which is what Nasmyth appears to be arguing for. What's kind of ironic is that in this paper he makes arguments about what could/should be happening in a cell based on notions like relative amounts of certain proteins and the rates of some reactions. That's a computational model, even if it's not explicitly expressed as a set of equations.

All that said, my personal goal is to end up with expertise in both computational and wet lab experimental work so I can alternate between doing biochemistry, genetics etc and computer modeling on my own [ie without relying totally on collaborators]. Now I just have to figure out what advisor/co-advisor combination is going to allow me to do that ...

[I wonder what Kim Nasmyth thinks of the branch of synthetic biology that doesn't even pretend to be interested in how cells "really" work but rather is intent on just building biological systems entirely from scratch.]

*Update: After thinking about this a bit more, I think Nasmyth misunderstands what's probably the most fundamental aspect of what's being called "systems biology". He seems to equate systems biology with mathematical models, whereas what systems bio is really about is looking at entire systems and trying to figure out how they function as a whole, instead of just characterizing the parts in isolation. Mathematical models are a tool that can help because it's hard to reason in a principled, consistent way about interactions between multiple components without math, but they're just a tool, not [necessarily] an end in and of themselves. I don't think any reasonable "systems biologist" would argue that experiments aren't incredibly important in understanding whole systems, much more so than computational models are at the moment.

As I mentioned above, I think it's ironic that Nasmyth rails against computational models when he's using one himself, albeit not explicitly. I think it's even more ironic that most "systems biologists" would probably look at the argument he lays out in his paper and say "That's systems biology !", because he's reasoning about various aspects of cellular mechanism that come together to make sure that chromosomes separate at just the right time during cell replication ie he's looking at how the system functions as a whole. He's doing the very thing he seems to despise so much.

Ok, enough about that now ;-) I think the biggest reason I felt compelled to write about this is because Nasmyth is a well-known and respected cell biologist, so it's a bit disconcerting to see him so [apparently] virulently opposed to the field I'm going into.


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