Biomedical computation in Biomedical Engineering will consist of three components: (1) image processing and pattern analysis, (2) data and knowledge base management, and (3) high-speed distributed computing of large data sets. These components will interact with one another while providing the enabling technologies for the analysis and utilization of the data produced by biomedical applications. Much of the data generated by biomedical systems appears in the form of signals (symbolic strings and waveforms), images, and, in general, arrays of vectors.
Part of the research effort required by biophotonics and nanoscale systems is in the area of computational models for the physical processes that generate the data. Research at UCI on computational models includes methods based on cubic and generalized spline approximation. Complementing the research on computational models for data generation is the UCI focus on pattern analysis. The objective is to develop application-specific algorithms for capturing and interpreting various complex patterns in the data.
Most biocomputational methods need to access and analyze large amounts of data. The data and information generated by such methods need to be tracked as time evolves. The nature of such scientific data/information demands the use of a powerful and intelligent database management system. Areas of current and future investigation include advanced data modeling, knowledge management, data mining, query optimization, and parallel/distributed processing of transactions.