computational biology: a lot cooler than you think

While the two images to the left remind me quite a bit of fried eggs died blue, they are in fact com­pu­ta­tional rep­re­sen­ta­tions of cells.

They come from the cover of of a new book, “Com­pu­ta­tional Methods in Cell Biology,” co-​​edited by chem­ical engi­neering pro­fessor Anand Astha­giri. Okay, so it may not be beach reading, but I assure you it covers a really inter­esting topic.

Com­pu­ta­tional biology has been around for decades,” said Astha­giri in an inter­view yes­terday. But only recently have we begun to realize the full poten­tial of its utility. And by realize I don’t mean like we woke up and a light bulb turned on, I mean realize in the sense that it’s actu­ally starting to happen.

Which is why Astha­giri thought it was so impor­tant to devote a volume in one of cell biology’s leading tech­nical series to the topic. He approached the edi­tors with his idea to develop a com­pu­ta­tion hand­book for exper­i­men­tal­ists in 2009 and it finally reached the light of day last month.

It will be a very good resource espe­cially now,” said Astha­giri. “It’s hard to train in cell biology without being at least aware of how com­pu­ta­tion can be used as a tool even if you’re not going to use it your­self at least to know what it’s capable of.”

The reason comes down to the emerging field of “sys­tems biology.” Net­work sci­ence, which I so love to talk about on here, isn’t lim­ited to just social net­works and mobility pat­terns. It’s starting to look like the “reduc­tionist” approach to sci­ence is no longer useful in many areas. Cell biology is no exception.

You can’t look at a single pro­tein and say it has a single effect on the rest of the body and that if you sup­press it with this or that drug it will work the same way for everyone. The reason is because the mol­e­c­ular, cel­lular and multi-​​cellular sys­tems that keep us alive (and effec­tively are us) are deeply inter­con­nected. Change this pro­tein and effect that pro­tein. Mess with this tissue, notice changes in that tissue.

Okay great, so where does com­pu­ta­tion come into all of this? Well, if you want to look at a system, even the system of a single cell, you’re talking about a whole lot of data. You can look at pro­tein levels, DNA sequencing data, imaging data you name it. Each of these presents a single tech­nical ques­tion with thou­sands of data points alone. Then if you try to inte­grate them with each other, as is often nec­es­sary when you take a sys­tems approach.…you see where this is going.

Without com­pu­ta­tion you can’t have sys­tems biology. And without sys­tems biology we can’t answer the kinds of ques­tions that are now arising around treating dis­ease and main­taining health.

Astha­giri and his co-​​editor, Adam Arkin, chose to orga­nize the book into three sec­tions: mol­e­c­ular, cel­lular and mul­ti­cel­lular. Then within each of those sec­tions the look at a variety of bio­log­ical prob­lems that can be addressed com­pu­ta­tion­ally. Each chapter tackles a dif­ferent ques­tion, giving both a high level and more in-​​depth dis­cus­sion of the com­pu­ta­tional tools involved. The authors of the chap­ters are leaders in their var­ious fields. Some are exper­i­men­tal­ists. Some are com­pu­ta­tion­al­ists. Some are both (Astha­giri is both).

Com­pu­ta­tional and sys­tems biology often involves a lot of col­lab­o­ra­tion. Because exper­i­men­tal­ists and com­pu­ta­tion­al­ists are not always one in the same. Already, just pro­ducing the book has spurred a new col­lab­o­ra­tion for Astha­giri, who is now working with Chapter 13’s author, James Glazier, who devel­oped a soft­ware package called Com­pu­cell 3D, which allows for the dynamic mod­eling of cells and groups of cells.

So, like I said, not beach reading but ridicu­lously cool.