dsarScience in the Seams

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.

—Lanny Liebeskind, Samuel Candler Dobbs Professor of Chemistry and Director, University Science Strategies

Vol. 10 No. 1
September 2007

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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.”

Staging Science
Teaching, and learning from, the interdisciplinary class

Thinking Outside the Pipeline
The impact of the unexpected in work-life issues

Creative Minds and "The Greatness Game"
A Response


Academic Exchange: Can you frame the CLS in the context of science and Emory’s goals?

Lanny Liebeskind: A revolution is taking place in computers, which can store and process more information faster than ever, and in computational science and techniques for managing and manipulating that information. At the same time, we are witnessing a revolution in the amounts of information that scientists can acquire about biological systems, such as the vast quantities of information contained in the genomes of living systems. There’s so much information that it’s impossible for a human to analyze it, to find patterns, to interpret, and to draw conclusions without help from computers.

At Emory, one of the core themes of the strategic plan is to advance new frontiers in science and technology. The Computational and Life Sciences Initiative (CLS), which is part of that theme, represents Emory’s strategic focus on the basic sciences and includes efforts to help position the institution for the future by being attentive to the marriage of computer hardware and software with analysis and understanding of the incredible amount of information that is being produced in the life sciences.

AE: How has the approach to scientific research changed over the years?

LL: In past decades natural science was tightly categorized into traditional disciplines such as physics, chemistry, and biology. The discovery of the genetic code in the 1950s led to a blossoming of the life sciences, and nowadays many scientists believe that the leading edge of discovery is at the intersection of the life sciences with the physical sciences and mathematics. Rather than “deconstructing” nature into its simplest parts, as scientists did for most of the nineteenth and twentieth centuries, the twenty-first century will likely be spent trying to understand, scientifically, the nature of complex interacting systems by “reconstructing” complexity from its component parts. In pursuit of that goal, scientists are trying to figure out how complex interacting systems work (for example, the interacting chemistry, biology, and physics of living systems). The tremendous progress in computer hardware and computational techniques and the ability to store, organize, and manipulate vast amounts of information allows scientists now to model and to carry out experiments on complex interacting systems.

AE: Could you give an example of computational science applied to a complex system?

LL: The human genome is like a book with an alphabet, words, sentences, grammar, paragraphs, and chapters. Suddenly we have deduced the whole structure of the human genome (DNA), a very, very big book, but we only know the alphabet, and some of the grammatical rules, and we have found some of the sentences. We might know how to recognize the alphabet and read individual words of the story, but we don’t know how to put the complete story together. How do we take the immense amount of information encoded in the human genome, which can’t be interpreted simply by looking at it, and figure out where the sentences and paragraphs are positioned, where the chapters begin and end, and then try to fully understand the encoded “messages” of those chapters? It’s to solve complex problems like these that the power of computers and computational science is a critical necessity.

AE: How will the CLS affect your work?

LL: My own research is focused in the fundamental synthetic sciences. My coworkers and I try to invent new chemical reactions that become the tools that other scientists use to build and transform molecular structure. For example, if you’re going to invent a new pharmaceutical drug to treat disease (as my colleague Dennis Liotta does), you need chemical “tools” to be able to modify the structure of a molecule, to selectively make bonds between separate molecules, to add atoms here and move them there, and thus change the properties of the end product. We invent the new chemical “tools” that people use to do that.

With regard to the CLS, I’m not a computational scientist, but I’m interested in science broadly, and have worked to see that it is supported and encouraged across the institution. I helped to give “birth” to the CLS and will continue to work to see that it represents a strong and visible home for basic science within the strategic plan.