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Stein Gives Bioinformatics Ten Years to Live

by Daniel H. Steinberg
02/05/2003

Lincoln Stein's keynote at the O'Reilly Bioinformatics Technology Conference was provocatively titled "Bioinformatics: Gone in 2012." Despite the title, Stein is optimistic about the future for people doing bioinformatics. But he explained that "the field of bioinformatics will be gone by 2012. The field will be doing the same thing but it won't be considered a field." His address looked at what bioinformatics is and what its future is likely to be in the context of other scientific disciplines. He also looked at career prospects for people doing bioinformatics and provided advice for those looking to enter the field.

What Is Bioinformatics: Take One

Stein, of the Cold Spring Harbor Laboratory, began his keynote by examining what is meant by bioinformatics. In the past such a talk would begin with a definition displayed from an authoritative dictionary. The modern approach is to appeal to an FAQ from an authoritative web site. Take a look at the FAQ at bioinformatics.org and you'll find several definitions. Stein summarized Fedj Tekaia of the Institut Pasteur--that bioinformatics is DNA and protein analysis. Stein also summarized Richard Durbin of the Sanger Institute--that bioinformatics is managing data sets.

Stein's first pass at a definition of bioinformatics is that it is "Biologists using computers or the other way around." He followed by observing that whatever it is, it's growing. He showed the results of performing searches in published papers of the last 20 years for keywords in titles of abstracts. As a baseline, over the last two decades the use of "cell" has roughly doubled while the use of "genome" has gone up by a factor of 10 from 1,000 papers per year to 10,000 papers per year. There were essentially no occurrences of "bioinformatics" before 1992. Since then it has grown to three orders of magnitude up to its current rate of 1,000 papers per year.

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Is Bioinformatics Really a Field?

The field has meetings, journals, and books. The problem, according to Stein, is that it is a tool and not a scientific discipline. Tools get absorbed into the greater disciplines. There are examples of disciplines defined by a problem domain contrasted with services defined by tools.

Robust scientific disciplines are often defined by a problem domain. For example, a development biologist studies the development of multicellular organisms using what ever tools are at hand. They aren't defined by the tools they use. A pharmacologist studies the interactions of chemicals with physiological properties. Similarly, physicists aren't defined by their tools; they study the nature of matter and energy.

On the other hand, services are defined by tools and they are often time-limited. For example, a microscopist knows how to use microscopes. Now that a microscope is a ubiquitous tool you won't find many specialists in this area. While a pharmacologist has a problem domain, a pharmacist knows how to compound medicines and fill out regulatory paperwork. There are fields that cross over. Stein offered molecular biology as an example of a scientific discipline that has transitioned to a service.

What Is Bioinformatics: Take Two

One of Stein's tests for a discipline is the "Department Of" test. Take your favorite field or service and prepend it with your favorite institution's name, followed by "Department of". For example, he is quite happy with the phrase "the Harvard Department of Genetics." On the other hand, a "Department of Microscopy" seems to him to fit better at an Institute of Technology. He said that for him, a Department of Bioinformatics has the same feel and he doesn't predict the establishment of bioinformatics departments.

Stein returned to the question, what is bioinformatics? In light of his thoughts on services defined by tools and disciplines defined by problem, his answer was simple. Bioinformatics is just one way of studying biology. Whether you think of bioinformatics as High Throughput Biology, Integrative Biology, or Large Data Set Biology, fundamentally Stein argues that bioinformatics is biology.

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Later an audience member asked Stein, "Is it strange when biologists never touch goosh: body parts, liquids.... Steins answer was, "No, they're studying life. Biologists like Ernest Mayer can sit in his office and look at other people's data and develop theories of selection. When people ask me, I say I'm a biologist."

Stein answered another question on whether biologists should be required to take introductory programming classes by saying, "Yes, the computer has become a central tool for biology like the microscope or the centrifuge. Being able to produce your own software for data analysis should be part of the undergraduate and graduate curriculum. In answer to a related question about computational biology, Stein answered that "it is algorithm development. It is a specialized discipline. I think it's a branch of CS."

How Do You Make It in Bioinformatics?

Two years ago there was a huge bubble in bioinformatics with students with BA's in biology who knew a little Perl or Java, or CS people with some biology getting offers for $50,000 to $60,000 per year for entry-level positions from pharmaceuticals and bio tech. More recently, the market has settled down. The 2002 New Scientist salary survey reports the median income for academic positions in bioinformatics is $75,000. This is comparable to the numbers for clinical biologists and slightly better than the numbers for cell biologists.

Stein has some simple advice for how you make it in bioinformatics:

  1. Learn biology. Investigate the problem domain for bioinformatics.
  2. Pick a problem that interests you. Don't just follow where you think the hot topic is or what seems to be an easy problem. Consider what you are willing to spend the next decade or two or the rest of your life working on.
  3. Know your tools. Don't treat your tools as black boxes. Understand how they work and what their limitations are. With a microscope you don't need to know optics, but you should know something about light paths, magnification, and resolution. Don't be afraid to use non-computer tools. Don't find the problems that fit your tools.
  4. Don't be ghettoized. If you expect to be a scientist and to be doing research then don't come in just to perform services to apply your tools to other people's problems. If you want to write software and provide a service, that's great but do so deliberately.
  5. Do it because you love it.

After taking time to look back at his own career, Stein advised the audience that "there is an event where you find your true avocation. It's easy to find yourself going down the wrong path. There's no shame in turning back." But, Stein said, when it comes to bioinformatics, "It's the biology stupid".

Daniel H. Steinberg is a podcaster, author, editor, trainer, and developer at Dim Sum Thinking. He co-authored the book Zero Configuration Networking: The Definitive Guide.

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