Grand challenges in biomedical computing.

Abstract

Advances in computing technology (both algorithms and hardware) over the next several years promise to make increasingly sophisticated computer modeling of biomedical phenomena a routine part of biomedical research. Improvements in both the absolute speed of processors and in their programming and graphics interfaces will allow nonexpert users to bring computing power equivalent to the supercomputers of a few years ago to bear on routine research problems and to display complex data in understandable ways (visualization). Although biomedical applications have traditionally not driven the leading edge of computing and supercomputing, such applications are increasingly being ported to advanced parallel and vector processors. This paper summarizes the current state of biomedical computing, citing examples of the best practice in research today. A number of projects enabled by advanced computing from various subdisciplines are described. Trends in technology for both inexpensive (workstation) and high-end computing (vector supercomputers and parallel processors) are cited; the implications of these for biomedical computing are discussed. "Grand challenges" in biomedical computing, i.e., computational problems of major scientific importance that are beyond our current capabilities but that might be achieved in a 5-year time frame, are outlined.