Major areas of research are: knowledge-based problem solving methods, clustering, and predictive data mining for bioinformatics, representation and inference for biomedical image interpretation, distributed collaborative problem solving and planning systems, multimodal interfaces and medical decision-making systems. In bioinformatics my major research is in the area of predictive data mining and clustering of macromolecular structural data. I am developing new techniques of spatial data analysis involving segmentation, clustering, interpretation and prediction of structural and functional classes of macromolecules. Current projects include: new algorithms for combinatorial clustering of RNA ribosomal data; new feature selection methods for characterizing conformational patterns of DNA, automated interpretation of multidimensional NMR data, methods for extracting the core of a protein structure in a family-specific manner, and techniques for multi-alignment and segmentation of proteins.      I am also coordinating a Strategic Resource Opportunity initiative in Bioinformatics which includes collaborations with the NDB Project headed by Dr. H. Berman in Chemistry, the NMR Interpretation Project headed by Dr. G. Montelione at CABM, and the Immunoglobulin Project headed by Dr. I.G. Gelfand at the Mathematics Department. These, and other projects with the Waksman Institute, DIMACS, and several academic departments, support and introduce advanced Computer Science methods into molecular biology and more generally into the Life Sciences.