10 No. 1
Science in the Seams
Computational and Life Sciences Initiative redefines disciplinary lines
High-performance computing at Emory
“Everybody understands or recognizes the combination of computational and life sciences as very promising. . . . Few people have been working in this combination of fields long enough to have established a leadership presence.”
“Rather than 'deconstructing' nature into its simplest parts . . . , the twenty-first century will likely be spent trying to understand, scientifically, the nature of complex interacting systems by “reconstructing” complexity.”
Thinking Outside the Pipeline
The impact of the unexpected in work-life issues
Creative Minds and "The Greatness Game"
Academic Exchange: Why is the CLS Initiative so important to Emory?
Vaidy Sunderam: The CLS has tremendous potential to advance science, and it is very close to what we do very well already. Obviously we have a very strong life sciences capabilities; we have a strong computational presence. By marrying them we can build on our existing strengths and create new strengths. We didn’t invent this, but everybody understands or recognizes the combination of computational and life sciences as very promising. Genomics is a classic example; X-ray imaging is a classic example. It’s all of tremendous importance. Many people are aware of this fact, but the field is still very new and progressing; therefore Emory can become a pioneer because few people have been working in this combination of fields long enough to have established a leadership presence.
AE: Computational science doesn’t immediately come to mind when Emory is mentioned. Are there “hidden” capabilities here?
VS: Yes, but at the same time there aren’t a whole lot of other places that come to mind when you think of computational science. Computational science is a unique discipline. When you say “computer science” a lot of people think of Stanford, Berkeley, MIT, Carnegie Mellon. If you say “mathematics” people say Princeton, MIT, Harvard, Berkeley, Michigan. But when you say computational science, it’s more of a set of niches. In circles like medical imaging, high-performance computing, computational chemistry, or genetic analysis, Emory is very well known.
AE: What’s the difference between computer science and computational science?
VS: Computer science is the science of making computers what they are, making them faster, interconnecting them in networks, making user interfaces that are easy to use, incorporating multimedia, accessing databases, and techniques to prevent viruses—everything that has to do with the computer itself. Computational science is the use of computers in physics, chemistry, medicine, etc., that brings together and applies the underlying mathematics using computational techniques. Any modeling and simulation system has to be founded on a mathematical model. If you have an X-ray image, how can you apply a computational algorithm to detect if that image shows a tumor or just a calcium deposit? You have to start with the basics of the underlying mathematics—how is each pixel is going to be represented, what is the characteristic of each pixel, what is the relationship between them? Then you develop equations and translate them into computer programs. The collection of those things—the application to science, the underlying mathematics, and the computer algorithm—those are the three components that make a project or a discipline called computational science.
AE: What could come out of the CLS?
VS: The CLS has three pillars. Computational science and informatics is the one that I know most about. CS & I is going to produce new knowledge in terms of new mathematical methods, new computer algorithms, and more precise and faster computer models of physical and biological phenomena. Synthetic sciences is another pillar of the CLS. Some of the developments that will come out of that can be described with the term “molecular machines”—ways to make molecules, proteins, and agglomerates of proteins behave in ways you want them to behave, and thereby go and do certain things. For example, if you could engineer a molecule that could eat cancer cells without destroying other cells in neighborhood, that’s an example of a molecular machine. The whole field is called synthetic science, because you’re synthesizing biological systems. Somewhere in the middle is the third pillar, systems biology, which is the science of understanding living systems across scales, from the molecular scale to the cellular level, to the organism level, to the system level, to the population level. Most people right now study a biological or living entity at one level, horizontally, but if you actually see the implications across the levels you get a great deal more insight into how a living system works.
AE: You’re talking about new drugs and vaccines, for instance?
VS: Absolutely. Drug discovery is a very likely and very specific outcome of new research in these areas. So is environmental science, though more from the standpoint of molecular machines than from the standpoint of population ecology. Bio-remediation is an example, such as engineering molecules that would eat up pollution in the air or ocean. There are some limited successes in those areas, but if we could do it in general, for instance develop something that could detect pathogens in the air, such as anthrax spores, and engineer something locally to destroy all those things, it becomes a new type of environmental science.