Sociologist Joan Fujimura has made a career out of observing your work
Joan Fujimura holds an unusual position in the genome field. She’s not sequencing genes, probing their function, or developing new technology. A sociologist based at the Institute for Advanced Study in Princeton, NJ, Fujimura is studying the process of genome research — looking at individual investigators, their laboratories, their institutions, and national programs. “It’s valuable to have someone who studies science cultures examine our culture,” says Larry Hunter, director of the Center for Computational Pharmacology at the University of Colorado Health Sciences Center. “We improvise a lot in our field, making things up as we go along. Having someone study this process in a systematic fashion might help us understand our blind spots and point to missed opportunities.”
Fujimura is now hard at work on a book about genome research in the United States and Japan. When she’s not writing, she’s often observing researchers in their labs, or accruing frequent flier miles between Tokyo and New York. GT spoke with her in Princeton before she departed on her latest trip to Japan.
GT: How did you become interested in the sociology of genomics?
Fujimura: As a graduate student at the University of California, Berkeley, in the 1980s, I studied the development of research on the genetics of cancer. I was intrigued by how quickly biological research in many different subfields was becoming dominated by molecular biology. Biology was becoming molecular biology.
In my new project, I am studying how people are making sense of all the information generated by the human genome projects in Japan, the US, and Europe. Data and new technology have been generated at an amazing pace, and now the job is to see what all these bits and bytes of information mean. Biologists alone cannot do this job because of the volume of information available, and computational scientists of all kinds have joined in this work.
This is where there has been some conflict, or what David Botstein has called the “two-culture problem” between biology and computer science. This conflict is changing now, as more students in each field are becoming familiar with the other science. But there are still differences in ways of doing the work and making sense of the world. These differences between the approaches to the work are part of what fascinate me.
GT: What lessons emerged from your study of cancer research, which culminated in the book Crafting Science?
Fujimura: Some scientists in the 1980s made grand statements about oncogenes, claiming that by understanding them we could devise interventions that would work on all kinds of cancer. As usual, things turned out to be more complicated than scientists had hoped for. There are so many different kinds of cancers, a single attack has not been possible.
I want to emphasize the complexity of biology, and this study is a perfect example of that complexity. Oncogene research today no longer posits a single “unifying pathway” for all cancers. Instead, researchers present a proliferation of genes and biochemical pathways by which cancers develop and by which intervention may occur. So complexity reigns again.
GT: What do you hope to accomplish in the genome field?
Fujimura: I want to emphasize the complexity of the science and the worlds that produce the science. I’m not studying science to make science the bad guy. I want to learn enough to be able to write critically about science when warranted, but also to talk about the things science is doing right — things that are pretty remarkable. I want to avoid and criticize the reductionism that is often used to portray science and scientists by some scientists and some social scientists.
GT: What are some of the biggest changes you’ve seen in biology over the past two decades?
Fujimura: For the longest time, biology was a cottage industry, proceeding on a much smaller scale than other areas of science. The Human Genome Project changed all that, creating the “Big Science” scene for biology. The HGP has produced a different scale of complexity for biology. Small lab-sized projects have been transformed into projects that are translaboratory, transdisciplinary, and transnational. How genomics researchers handle this scale of complexity is also fascinating to me.
In addition, private industry has moved into the field in a big way. Biological research is occurring in industry on a much larger scale than in the past, and there are far more alliances these days between universities and corporations. All of these new alliances — between academia and private industry, between biologists and computer scientists, between national projects — produce a different kind of complexity for genomics, a complexity that has to do with many different cultures of science trying to work on the “same” problem.
This has happened before in history, with the physicists and chemists moving in to study biological problems in the early part of the 20th century. But today’s situation is slightly different. Biologists need computational assistance, and computational scientists need biological expertise in a way that differs from the situation in the early part of the century. So their working together across “cultures of science” is one of my objects of study.
GT: What have you learned from the Japanese example?
Fujimura: Because Japan’s program was so much smaller than the US effort, one computer science laboratory at the national Human Genome Center in Tokyo was given the responsibility of connecting all the genome biology laboratories across the country. So in a sense, they also became responsible for trying to teach biologists what they could gain from computational techniques. There’s no way that could have happened in the US because there were too many genome laboratories. This is just one example of the scale differences between the projects in the US and Japan. There are also differences and similarities in the ways that people negotiate their working relationships, partly because of scale differences and partly because of different cultural histories. I am writing about these in the new book.
GT: Now that genome research has become such a vast enterprise, are more people trying to do what you do?
Fujimura: Scientists are so busy with their research, they don’t have the luxury to study their own work process, their own process of producing knowledge. On the other hand, many social scientists haven’t made the investment to learn the science, which you need to do to discuss the field in an informed way. But lately, more people have become interested in writing the ethnography of genetics research. That’s good because there’s a lot of work to be done.