DESCRIPTION (provided by applicant): We have designed a training program for PhD students in Bioinformatics, Genome Technology and Computational Biology. Once it became apparent that modern biology would be increasingly dependent on quantitative methods, several approaches to training arose, largely as a matter of necessity rather than planning. Some of these, characterizes as teaching experts in one field the competencies of the other, were important when the field was changing to quickly to train a new cadre of researchers in a completely new field that had not yet been crystallized. This activity remains important, but is no longer sufficient. Mathematicians operating in the traditional context of academic mathematics departments will continue to learn biology and make contributions to its development. Laboratory biologists will similarly acquire competence in the statistical and computational techniques necessary to make use of genome technologies. But we are convinced of three key things: 1) that the greatest contributions in the field will be made by a new breed of researcher trained in computational biology per se, 2) that the time to begin such a training effort has arrived, with a substantial number of very bright undergraduates proactively pursuing double majors in the mathematical and biological sciences or similar interdisciplinary education, 3) perhaps more controversial than the other two, that mathematical talent is relatively rare, and that mathematical training requires substantial effort on the parts of both student and teacher. Thus, our program builds upon a solid foundation in statistics, and computer science, while providing direct integration into experimental biology laboratories, clinical research programs, and the culture of the life sciences.