Computer pattern recognition techniques have been developed for general use and have been applied to a variety of problem areas. The first version of a display-oriented pattern recognition program for the DEC-10 computer has been completed. It includes algorithms for feature selection, feature reduction, and cluster analysis. The package now includes ten algorithms, and about 20 more will be added in the coming year. An improved algorithm for nearest neighbor classification, one of the most successful techniques for pattern classification, has been developed. Cluster analysis techniques have been applied to a variety of data, including compounds used to treat epilepsy, in an attempt to determine which chemical properties of the drugs are important in making them effective, and grants data, to look for relationships among the many disciplines receiving NIH grants. A study of laboratory automation, which includes some of the pattern recognition methods used for laboratory data, has been completed. BIBLIOGRAPHIC REFERENCES: Shapiro, M.B.: The choice of references points in best-match file searching. Comm. Assoc. Computing Machinery, 19, 6, 1976. Shapiro, M.B., Schultz, A.R. and Jennings, W.H.: Computers in the research laboratory. Ann. Rev. Biophys. Bioeng. 5, 177-204, 1976.