Genome mappings have generated a vast amount of biological data and now more than ever, scientists need sophisticated computational techniques to make sense of it.

For example, the Human Genome Database contains approximately 3 terabytes of data and the volume of life sciences data is doubling every six months.

To meet those ever-increasing needs, bioinformatics is shifting from software designed for a specific project in academic laboratories to the commercial mainstream.

Eric Jakobsson, director of the National Institutes of Health’s fledgling Center for Bioinformatics and Computational Biology, divides bioinformatics into roughly three categories: the application of principles of physics and chemistry to the modeling of biological systems at the atomic and molecular level; dynamical systems modeling, that is, representing how biological systems evolve as differential equations or stochastic processes; and pattern analysis, the process of searching for patterns in sequences of genes or proteins to gain insight into how a biosystem works.