Modeling and artificial intelligence approaches to enzyme systems.

These include performance of serious modeling on laboratory microcomputers, e. g. IBM PCs such as fitting models to kinetic data with linear or nonlinear regression and graphical assistance; use of PC to rapidly build multienzyme models of metabolic systems, which have previously taken much longer on large computers; use of PCs to build data bases used for modeling; extraction of information from models by sensitivity analysis; and use of the preceding to design experiments. Artificial intelligence techniques permit critiquing and evaluating the data, experiments, and hypotheses being modeled. Much of the modeling process can be stated within the framework of expert systems (now becoming available on microcomputers) using sets of rules for fitting and evaluating models and designing further experiments. Such expert systems can supervise calculations in addition to performing reasoning.