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By Michael Goldman

 
Leroy Hood
Nov. 12, 2002 | The young field of systems biology endeavors to consider processes in a broad context, measuring, perturbing, modeling, and measuring again, then refining the models until they are truly predictive in nature. While in silico biology comprises the modeling and simulation of systems computationally, systems biology is broader in scope, involving making laboratory measurements and running actual experiments.

Using a simple metabolic pathway in which kinetic parameters are known, Eberhard O. Voit of the Medical University of South Carolina poses this question: What is the best way to manipulate the concentration of a given metabolite? Human instinct, he contends, simply can't examine all of the scenarios quantitatively and determine which approach will produce the best outcome with the fewest side effects. But a simple computer model can. Thus, specialized expertise in model building is now essential, along with biochemistry and physiology. And these computationally intense models will require unprecedented computing power.

Nat Goodman of the Institute for Systems Biology (ISB) in Seattle observes that biologists have always stepped back and looked at problems from a systems perspective, even though their own detailed research might be restricted to a simple isolated reaction or metabolic pathway. The difference now is the vast quantity of genome-derived data — sequence, expression profiles, and so on. Describing the expression of a single gene in a range of tissues once took weeks. Now, data on tens of thousands of genes can be obtained within hours.

Systems biologists pride themselves on the study of that which is too complex to be reduced to its component parts. The very approach of studying something through computer simulations suggests that scientists think they can model a system adequately, and deterministically, by a collection of equations running on silicon chips — a reductionist notion, indeed.

 
Network news: The ISB's Eric Davidson and colleagues have modeled the development of the sea urchin endoderm and mesoderm.

Leroy Hood, one of the champions of the Human Genome Project and co-inventor of automated DNA sequencing (see "All Systems Go at ISB," June Bio·IT World, page 38), now thinks beyond the linear information in the DNA code itself. Hood is director and president of the ISB, the work of which he hopes will help unravel the complexity of interacting genes and proteins. Unconvinced that the necessary long-term interdisciplinary approach would succeed in an academic setting, Hood founded the nonprofit ISB just minutes from the University of Washington's School of Medicine, where he formerly held an academic appointment.

The institute is working with a variety of model organisms and representative pathways. In one study published earlier this year in Science, Eric Davidson, Hood, and colleagues used a systems modeling approach to construct a genomic regulatory network for development in the classic sea urchin. Their study involved the endo16 gene, which is regulated by two regulatory DNA sequence modules and nine sequence-specific transcription factors. The model accounts for external (positive and negative) inputs and for perturbation of the system by mutation. The model correctly predicts the endo16 regulatory system response under all conditions tested. The goal of a full description of development is clearly far in the future, but this work serves as an inspiring model for more extensive studies.

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