Wanted: Hot Industry Seeks SuperGeeks: To Build Better Drugs, the Exploding Field of Bioinformatics Is Looking for Highly Trained Workers Comfortable with Supercomputing and Biology
Stone, Brad, Newsweek
Craig Benham has a problem. As a professor at Mount Sinai School of Medicine in New York, he trains students in the exploding new field of bioinformatics--the fusion of high-powered computing and biology that is aimed at revolutionizing the health-care industry. But Benham can't keep a postdoctorate researcher for more than a year. They keep leaving for jobs that pay up to $100,000 at bioinformatics start-ups, giant pharmaceutical companies or technology giants like Motorola and IBM that are targeting the rapidly growing life-sciences field. "These companies need a whole new class of biologists who have training in the computational and mathematical methods," Benham says. "I've got one former student who has been hired four times in three years, increasing his salary 30 percent each time. There's huge demand for these skills." Benham knows of what he speaks: this summer he will join the University of California, Davis, heading up its new $ 95 million bioinformatics program.
Bioinformatics encompasses its more widely known offspring, genomics, the study of genes and their function. It involves the use of supercomputers, vast databases and complex software to analyze the mountain of data that has emerged from the sequencing of the human genome, whose mapping was completed last summer. The Human Genome Project was a decadelong effort that cataloged 3 billion DNA base pairs--the chemical components that together spell out the genes that make us who we are. But the data that were supposed to change the world are merely three gigabytes of raw letters, a jumble of A's, T's, G's and C's (which stand for the chemical ingredients of DNA). The pairs of letters offer few hints about the genes they describe or what those genes actually do in each of the billions of cells in the human body.
That's where bioinformatics comes in: making sense of the genome by offering the tools to mine the data and match the DNA info with the genes. Venture capitalists invested more than $700 million in the field last year, according to the tracking firm VentureOne. Dozens of schools, including UCLA, have started bioinformatics centers in the past few years, and tech giants are targeting it as one of the few growth sectors in today's economy. IBM in particular recently estimated that selling computer equipment to the life-sciences industry over the next three years is a $43 billion opportunity. Eventually, the proponents of bioinformatics claim, the new field will change health care by allowing pharmaceutical companies to shave years off the drug-discovery process, and letting doctors tailor medicines to an individual's genetic makeup. "This is as big an opportunity as the computer industry itself," says Nathan Myhrvold, once the chief technology officer at Microsoft and now a Seattle-based investor who concentrates on biotechnology. "In order to understand how our bodies work, we need to process enormous amounts of information."
But the fledgling field first must find the right people to build, deploy and manage such complex systems. One study estimates the industry will need 20,000 highly trained workers by 2005--a new brand of super-geek who understands the complex tongues of both biology and computer science. That person will look a lot like 26-year-old Marcin Joachimiak. The fourth-year Ph.D. candidate at UC, San Francisco, has bounced from a mathematics undergraduate program to a biomolecular lab and ended up pursuing his doctorate in biophysics. He spends his days peering into a computer screen at the cellular and molecular pharmacology lab of Prof. Fred Cohen, analyzing the DNA of the deadly parasite that causes malaria. The ultimate goal: identifying which sequences are most vulnerable to attack by drugs, and then sending those new, promising targets into the lab. "This is not computation in a vacuum," says Cohen. "Analyzing the data leads to more focused experiments," which have a better chance of success than trial-and-error tests on animals. …