Adding modeling in the wet lab

Submitted by mattions on Mon, 05/19/2008 - 15:52

Crossposted from YANNB

Modeling in biology is a kind of Cinderella branch of the field. Is not central as it is in physics and there is a lot of skepticism about it, especially from the wet lab guys. Biology has started as a descriptive subject and then it went to the quantitative approach.

Quantity. That’s exactly what you need if you want to do some modeling, that at the end of the day is crunching some numbers using a computer.

Let me just make a comparison with the engineering field. This guys usually:

* think about an idea
* model it to test if it’s worth to build it and it will resist
* build it in the reality

If for example you’re building an house, you hit a button and the program is going to make all the calculation to see if the house is safe and it will last, or it will just collapse under its own weight. Actually you’re testing your idea, modeling it on a virtual space.

In biology you have the same kind of approach:

* think about a question
* design the experiment to try to answer the question
* do the experiment

The modeling should be one point of the design part to let you know if your experiment would discover something or not, so you can save time and know on which parameter focus your attention or which proteins seem to be the important key role. It should help the biologist to design better experiment.

For example you have a cascade signaling involving something like 15 proteins. If you have a tool that is going to predict that the most interesting reaction over there involve protein 2 and protein 3 you can focus your attention over there, avoiding the scan of all the other proteins in the first place.

To do that we need of course a really rock-solid modeling framework and from the other hand a really easy and fast way to use it.

We are quite far from there, but it looks to me like an intriguing prospective.

hmm..

Submitted by Leo on Tue, 05/20/2008 - 00:44.

I'm a lot more skeptical of this compared to the biocompass..

In engineering, you're dealing with the macroscopic scale, where you can describe all the forces at work with a (relatively) simple and manageable model without making almost any assumptions. At cellular scales, everything is stochastic, we don't know all the things at work, and even after making a lot of simplifying assumptions, modelling is still damn hard. We need to know a _lot_ before we can reliably predict the effect of any parameter in a cellular system.

I believe the approach you describe is feasible in individual domains, but not as a grand scheme of things, not until we have a complete 3D state of the cell we can computationally manipulate (and do it fast!). There are some places though where you can abstract the process and make the modeling reusable, and many of them give rise to nice bioinformatics tools.

And in real life, I think biologists use this approach every day - the modeling bit is just a mind experiment that will tell them whether the particular experiment is worth performing. But you're right that steps that take us closer to more rigorous and quantitative approach to modelling will be very useful.