For purists, the term simply describes the use of computers to handle biological information. The "informatics" becomes the manner in which computer software manages databases and assembles, extracts and displays information, which could include information from patient X-rays as well as protein arrays.

Others, the middle-grounders, go a step further and contend that the term applies to the mathematical, statistical and computer methods that actually solve biological problems, such as determining the correct amino acid sequences that make up a protein or that show how they fold into shapes of dazzling complexity.

Still others, the big-tent types, believe that bioinformatics is a science unto itself, one that develops computer databases and problem-solving techniques, known as algorithms, for the purpose of speeding up and enhancing biological research. In this definition, bioinformatics is the product of an entirely novel integration of mathematical, statistical and computer methods and the application of those approaches to address important biological questions.

Of course, the existence of such a word implies that something new has happened to demand its creation. Yet "new" is a relative term when it comes to science. In this case, bioinformatics stands at the end of a process that began more than 70 years ago with the introduction of electrophoresis, a technique that allowed proteins to be separated in solution. Other key moments along the way include the discovery of recombinant DNA techniques and compact discs, the early networking of computers and the commercialization of Internet technology. The first crescendo came in late 2000 with the publishing of the human genome (a consequence of bioinformatical computing power), the blueprint of genetic instructions that result in the growth and development of human beings.

Sorting through these instructions, crudely akin to being given 150 million pages of a book with no punctuation, page numbers, chapters or headlines, and being asked to make sense of it all, requires something more than a clever guess. It requires a big computing mind, capable of seizing large chunks of data to find patterns, make comparisons, selectively organize and illustrate via graphic models. And it requires human minds to ask the questions, interpret the data and come up with answers to how life works and how disease arises.

So, be they middle-grounders or big-tent types, bioinformaticians -- who hail from such diverse fields as biochemistry, physics, mathematics, pharmacology and biology -- understand that their world view straddles computation, biology and information infrastructure in ways that are fundamentally different from the world view of scientists just two or three decades ago. No longer do they need to focus laserlike on a single gene or protein. They can think big because the knowledge base (or database) is exponentially bigger and because the technology to explore this knowledge is getting bigger still.

Computers, not microscopes, are the tools of this trade, yet the goal is the same: To discern and discover. "Bioinformatics" may not roll off the tongue, but as the field exposes the roots of everything from diabetes to aging, the word will soon be on even a layman's lips.