Predoctoral Training Bioinformatics/Computational Biol.

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DESCRIPTION (provided by applicant): Stanford University has a strong record of training in both the biomedical sciences as well as computer science and engineering. It has hosted a degree program in Biomedical Informatics (BMI, formerly called Medical Information Sciences) since 1982, which has been a valuable proving ground for training at the intersection of biomedicine and computer science. With the increased demand for scientists with credentials in biocomputation, Stanford recognizes the need to greatly increase its capacity for training at this intersection. A faculty retreat in January 2000 involving more than 70 faculty (from the schools of Medicine, Engineering, Humanities & Sciences, and the Stanford Linear Accelerator) began a planning process that has lead to a two-part plan for organizing graduate training in biocomputation at Stanford. First, the size and the scope of the BMI degree program will be increased by expanding the research agenda to include six strategic areas identified by the faculty: (I) structural and functional genomics, (2) biomechanical simulation, (3) computer assisted interventions and robotics, (4) image acquisition and processing, (5) computer-assisted instruction and networked education, and (6) informatics, data modeling, and statistics. Second, the expanded BMI degree program will be used as a focal point for integrating students in disciplinary training programs (such as biology, genetics, computer science, or mechanical engineering) into the biomedical computation training environment. These mechanisms will include the creation of cross-disciplinary courses that teach fundamentals of biomedicine to technical graduate students, and teach fundamentals of these technical fields to biomedical graduate students. It will also include activities designed to encourage transfer of knowledge between BMI and disciplinary graduate students. The training grant will therefore fund both BIM students and disciplinary degree graduate students for an average of 3 years, and provide mechanisms for creating a cadre of young, well-qualified scientists equipped to tackle the scientific challenges that arise in the 21st century.