In the fall of 1999, the Stanford Microarray Database booted up, and a level of computing power was suddenly available to the field of molecular biology that only a few years earlier was inconceivable. On Oct. 19, the database recorded its 50,000th experiment, marking its place at the forefront of an information processing revolution that has yielded groundbreaking insights into the relationships between genes and illness, as well as fundamental biological discoveries.
Microarrays, developed in the lab of biochemistry professor Patrick Brown, MD, PhD, in the early 1990s, took molecular biology by storm. They're small slides spotted with fixed samples of DNA, each for a different gene. When a researcher prepares a labeled cell extract and incubates it with the slide, messengers in the sample stick to the fixed DNA, showing which genes in the sample are active. Microarrays are especially useful for comparisons between normal and cancerous tissues or between different stages of development. Researchers use them to nose out the genes associated with such changes.
The problem, however, is that experiments with microarrays yield vast amounts of data. "Microarrays allow researchers to do in six months what previously would have taken six years of concerted effort," explained Gavin Sherlock, PhD, assistant research professor in genetics, who has been involved in the Stanford database from the beginning.
The need for the university database became apparent in the late 1990s after Brown and David Botstein, PhD, former chair of the genetics department, had put together a database for their own microarray results. They soon found that they needed something more sophisticated. Efficient processing and storing of microarray data, as well as the ability to easily retrieve and compare data with other experiments were all required. New information about genes spotted on the slides is continuously di
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20-Oct-2004