the design and specification of database and information systems, not merely their internal structure.
Graph theory and combinatorics are at the heart of many of the successful applications of mathematics and computer science in high-throughput genomics research (microarray chips) and rational drug design; the panel believes that this interface will continue to grow in importance. Computational geometry and the ability to describe, visualize, and computationally compare complicated surfaces in space will become an important area in proteomics and computational medicine.
Standard texts either need to be revised or replaced by more quantitative texts. The texts for most courses in elementary discrete mathematics are not especially exciting. They are filled with definitions but do not challenge the students with interesting problems. More exciting courses are taught by Stephen Rudich at Carnegie-Mellon and by Alistair Sinclair and Umesh Vazirani at Berkeley (CS 70). Terry Speed at Berkeley has developed an introductory statistics course in which the motivating examples are drawn from genomics.
It should be possible to develop courses in discrete mathematics, probability, and algorithms that emphasize applications in biology. It is particularly easy to find motivating examples from genomics and genetics, since those subjects are inherently combinatorial and probabilistic. As one example, sequence alignment is an ideal vehicle for introducing dynamic programming. Graph theory can be linked to sequencing by hybridization. Pedigree analysis and the design of genetic crosses abound with combinatorial puzzles. Probability can be illustrated through the analysis of sequencing and mapping strategies or pooling designs. Fred Roberts at Rutgers has done excellent work in this area (The Scientist 9, July 10, 1995).
There are not many programs designed specifically to impart quantitative literacy to biology faculty. Some existing programs target other audiences, such as quantitative training of K-12 students, high school teachers, predoctoral students, and postdoctoral students. Joe Rosenstein at Rutgers and Maria Klawe at the University of British Columbia are very active in developing such programs. In addition, The Keck Center in Houston, with sponsorship from NSF and NLM, runs a computational biology training program for predoctoral and postdoctoral fellows. A summer short course might be an appropriate vehicle for enhancing the quantitative lit-