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Kenneth Buetow, Director, NCI Center for Bioinformatics

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AT A GLANCE

PhD in human genetics, with an emphasis on biostatistics, from the University of Pittsburgh School of Public Health.

Played a role in the construction of the high-density human reference linkage map at the Cooperative Human Linkage Center.

Enjoys spending time with his children and family.

QWhere will bioinformatics be in two years? Five years?

AIn the shorter term I see bioinformatics evolving to be more intimately tied to the experimental process. Much of what bioinformatics does right now is in a linear model: We are either involved in the beginning of an experiment in terms of generating a hypothesis or at the end of an experiment in terms of trying to interpret the outcome of it. I see bioinformatics evolving to work in a more circular or spiral model — where bioinformaticians will be involved in both the development and interpretation of the hypotheses in an intimate link with the biologists performing the experiments.

In the long term I think bioinformatics is going to shift out of its centralized bioinformatics context and find itself more substantially placed in the biological context. What we’re going to see is bioinformatics not being as much of a separate entity as it becomes much more integrated into the academic disciplines of which it’s a member.

QWhat are the biggest challenges the field of bioinformatics faces?

AIt actually faces several major challenges. One is that it continues to be very expensive. We face the challenge of communicating that we’re actually not in competition for resources with our biological colleagues.

Another challenge is getting enough people in the game. There’s lots of recognition that bioinformatics is an important and developing field, but we still have way too few people who are practitioners of the art. Everybody agrees that we want to have more bioinformatics, but nevertheless the sort of quantitative people who are necessary to do it are sometimes perceived less glamorously than the people who are turning the tubes, running the sequencing gels, or performing the microarray experiments.

QWhat do you see as the most important task for bioinformatics to address beyond genome sequencing?

AWe have to move aggressively into translating the information that is part of genomics into the other contexts of biology and biomedicine. There’s been this big promissory note generated by many people who have said that with the appearance of the genome sequence all of biology will be different. It’s really critical that we figure out how to do the annotation and value-added information linking and integration that will allow the translation of genomics into therapeutics and prevention strategies.

QHow do you compete with companies to attract and retain qualified bioinformaticists?

APart of the way we do it is in recognition that what we do is different than what companies do. Our number-one priority is not profit or shareholders. The satisfaction in the work that we do comes from the derivation of new information and the sharing of that information. We also appeal to people’s better angels — to paraphrase Lincoln — in the sense that what we’re doing is for the public good.

QHow would you compare the quality of publicly available and commercially available bioinformatics products?

AAt times they’re apples and oranges. The public efforts are intended to be leading-edge applications, deployed with nowhere near the polish or the shrink-wrapping that a commercial concern has to have in order to survive in the marketplace. Our tools tend to be more innovative, but sometimes less robust.

QWhat non-existing technology do you most wish you had? What’s missing from the bioinformatics toolbox?

AWe are still missing substantial tools in natural language processing and the ability to extract scientific information from the very large collection of text-based literature that exists out there.

QWhat made you decide to enter a career in bioinformatics?

AMy training is actually in population genetics. As a function of having these large volumes of data on populations, we actually needed computer-based tools in order to make any sense of it.

I wouldn’t say I ever made a conscious decision to be a bioinformatician; I just ended up being described as a bioinformatician as my research matured.

 

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