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Systems biology, in search of a metaphor, tries out language of machines, intestines

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Sociology professor Joan Fujimura, visiting MIT from the University of Wisconsin at Madison, discussed her recent work at a Program in Science, Technology and Society (STS) colloquium on April 23. Formerly a specialist in anthropology at Stanford, Fujimura has since focused her attention on the sociology of science, particularly notions of nature/culture and science/society in the fields of genetics, bioinformatics and systems biology in the United States, Europe and Japan.

"One of the emphases in my frame," said Fujimura, "is to use ecological understanding from symbolic interactionism in my research," and she feels that "systems biology mirrors a lot of the kind of theoretical and methodological problems that we have in STS." As she noted, "Our problem"--in STS as much as in systems biology--"is how to represent complexity and still say something interesting and coherent."

Systems biology is a rapidly changing field, one that even its practitioners cannot define to mutual satisfaction. "They are explicit about their ontological problems," Fujimura said. Some scientists use the term "systems biology" loosely to apply to projects exploring individual biological networks. Others see it as an outgrowth of theoretical models derived from systems theory, mathematics, statistics, artificial intelligence, robotics, engineering and similar fields.

As Fujimura explained, molecular genetics started off a couple of decades ago with great optimism and the idea that, once the sequencing of the human genome was complete, diseases like cancer and type 2 diabetes would soon be cured. Something of a malaise fell over the field at the end of the 1990s, when it became clear that the Human Genome Project was not going to solve all of our medical problems, and that biological systems were massively more complicated than the older "one gene-one trait" model had foreseen. One result has been the proliferation of "omics"--e.g. proteomics, metabolomics, glycomics--as the study of the genome splinters into dozens of subspecialties.

Are biosystems engines?

Biologists looking for ways of thinking about the complexity of living systems have reached, in Fujimura's view, into two very different repositories of thought. One is largely mechanistic, and its language is drawn from control theory and machines--using terms like "circuitry," "modularity," "redundancy" and "robustness," which are also used to describe cars, electronics, traffic, robots and airplanes. For example, one prominent systems biologist, Hiraoki Kitano, used a schematic of a Boeing 747's hydraulic control systems to model biological systems. This reductionist model has begun to look less useful as we become increasingly aware of the complexity of living organisms.

Or are they intestines?

The other line of thinking, exemplified by British scientist Jeremy Nicholson, looks to natural ecosystems as models. His work, said Fujimura, could be summarized as "diverse, dynamic and intestinal," exploring the multitude of microorganisms that inhabit and indeed largely comprise the human body. Again, speaking of systems biology as a mirror of STS studies, Fujimura noted, "I would argue that we are now witnessing the reintroduction of time, place, interaction, multiple actors, history, environment, dynamics and diversity into what previously had been this timeless, unsituated and unidirectional picture of reductionist molecular genetics."

Fujimura has had a busy semester at MIT, interacting with colleagues in the area while teaching two courses, one on the development of systems biology and another that examines how the notion of population is conceptualized and operationalized in human genetics research. In a recent e-mail, she remarked, "At first, I was concerned about the effort of moving here for just one semester, but I am so glad that I did!"

A version of this article appeared in MIT Tech Talk on May 2, 2007 (download PDF).

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