In 2002, I was hired into the nascent Bioinformatics Masters Degree Program at Brandeis University as a part-time instructor, by Lydia Gregoret who was then the chair. I was (and am) working in the biotech industry, and the faculty model for Brandeis is to have bioinformatics taught by people working in the field. Lydia, Valerie Gregor and I crafted the first biology-based courses that would be offered as part of the Bioinformatics Program. In 2003, I proposed a Computational Systems Biology course for our second-year Masters students. We started offering this course in 2004.
While visiting California for an educational workshop on computational biology, I mentioned to Doug Brutlag that I was starting to teach a systems biology course, in a 3-hour-a-week, 10 week format. He thought I was a little crazy. Systems Biology, he told me, was probably too huge a subject to distill down into one semester, let alone a 10-week night-school format. Doug was right—we could probably do better than a 10-week survey course, but it’s a necessary introduction into a field that’s growing by the week, let alone the year. I think the course works as well as it could. The problem facing me now, as I get ready to teach it next semester, is in keeping up not only with what is advancing in the field, but also keeping up with what people define as systems biology.
The field of computational biology has evolved quickly over the past five years. I’m now the Program Director in the Bioinformatics Program, and here at Brandeis, we will undoubtedly face the challenge of developing our bioinformatics curriculum to be more geared towards modeling and systems biology. We want one of our objectives to be re-training biologists and other scientists on how to be computationally literate—in a range from sequence analysis to flux balance analysis.
It’s hard to say where to draw the line, though, for what’s important to systems biology, when it seems to encompass, at this point, everything under the sun.
While it once seemed silly to try to put systems biology together in a 30-hour semester, these days, it seems nearly impossible not to get a lot of systems biology buzz at every conference. Systems biology can now be summed up into the “Four M’s” buzzwords on single slides.
It’s getting so that it’s impossible to keep up with the rush towards systems biology around Boston these days. An acquaintance of mine at Brandeis noted that he had recently spent three separate meetings with three different groups of people—from three different consortia on systems biology in the last month alone. Whole departments are being set up in industry and academia based around this “systems biology” paradigm. While I think it’s a great idea, it seems to me like anyone who’s analyzing high-throughput data these days has stopped using the words “computational biology” or “bioinformatics” and has just started coupling the informatics with experiment and renaming the whole enterprise “systems biology”. That’s not what I’m concerned about, though. I’m concerned about the backlash that might occur when the first flush fades away.
I’m a little suspicious, always, of the “flavor of the month”. Systems biology seems to be the flavor of the month in the Boston area, at least. It feels too much like the big rush towards bioinformatics ten years ago. Bioinformatics will soon be dead if you believe Lincoln Stein. Maybe bioinformatics will be dead because everyone will start re-labeling all of its work as “systems biology”, but I don’t see any danger in computational biology or bioinformatics vanishing, no matter how you define them.
Work in systems-level biology isn’t new. In fact, there have been many good projects active in the field for years, headed by people like Hiroaki Kitano, Masaru Tomita, Eberhard Voit, Andreas Wagner, Michael Savageau, Bernhard Palsson, George Church, Trey Ideker, Leroy Hood — and so many others I’m leaving out and saving for another post. For those of you just starting in systems biology, those names are a good place to start your reading if you’re interested in the field.
They’re also good people to learn from. Scientists and decision-makers should look carefully at the challenges faced by those groups over the past decades and then learn from them. Systems Biology can deliver interesting science, but it’s a slower type of delivery compared to what might be expected in the shorter term. Systems Biology is going to be a long-term process. Our expectations should match up with the experience of seasoned systems biology scientists.