Thomas Pollard — Computational Approaches in Biology

(image reproduced from: https://blog.f1000.com/2017/02/01/f1000prime-f1000prime-faculty-launch-bioinformatics-biomedical-informatics-computational-biology/)

LC: I wanted to ask about the increasing role of computational techniques in biology. You’re in cell biology, which is not something people would typically think of as something you do on a computer, but I’m sure that modeling is hugely important in cell biology. 

TP: Yes, so let’s look at the historical perspective on this. Forty years ago, the people who were trying to do modeling in cell biology had almost no impact because not enough was known to make reasonable assumptions for a model and computers weren’t very powerful. We used to have a computer in the lab as big that cabinet, it had 48k of RAM. That was thirty, thirty-five years ago. Well the material required to do modeling and the computational power required to run it weren’t available, and this persisted until relatively recently. It was after the turn of the century that finally the computational approaches to cell biology questions actually started to have some traction. The first examples were very well characterized systems like bacterial chemotaxis and studies were done putting together what they knew about the biochemistry to explain the phenotypes observed in cells that had been mutated. 

Those pioneering studies were quite successful. In fact, their predictions were better than the experimental data after people went back and redid the experiments. About the same time, people started doing cell cycle models that were widely disregarded by geneticists, but they actually got most of the things right. In the 1990s, someone did the models of whether the actin systems can produce enough force to make a cell move. Since then, the field has really taken off. Twelve years ago we did a search for a theoretical person in the lab. Not everybody thought it was a good idea to hire a theoretician, but man he had a huge input and now we are going to have this quantitative bio center. It’s going to be a huge chunk of this new building over here. He’s the node from which it all started. And now we have multiple people whose main tool is computer modeling and biological systems. 

Do you think the place for people who are not interested in computation in biology is going to diminish as a result, or do you think there is just a growing potential for people with computational skills?

Oh no they’re going to need it, and everybody is going to be interested in it. Most people won’t feel comfortable inventing new mathematical methods, but the software is fabulous and so anybody who can click on a mouse can do computational biology now. There’s a beautiful thing at the University of Connecticut where you can make models of your reactions by just typing and clicking and you can even put it in a cellular context, the shape and size of your cell. You push a button and it’s got a super computer there that runs the mathematical models and send you back an answer five seconds later, it’s very simple. 

It’s like anything else. The cell biologists of the 60s didn’t do biochemistry; now everybody does biochemistry. The cell biologists of the 70s didn’t know how to do molecular biology, and now everybody does molecular biology. 

So in thirty years everybody is going to be doing computational biology?

Everybody is going to realize that if they really want to test their hypothesis, they’re going to have to make a mathematical model. And the future is almost now; we’re very close.

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