Predoctoral Training Bioinformatics/Computational Biol.

描述（由申请人提供）：斯坦福大学在生物医学科学以及计算机科学和工程方面都有很强的培训记录。自1982年以来，它已经主办了生物医学信息学（BMI，以前称为医学信息科学）的学位课程，这已经成为生物医学和计算机科学交叉培训的宝贵试验场。随着对具有生物计算证书的科学家的需求增加，斯坦福认识到有必要在这个交叉点大大增加其培训能力。2000年1月，70多名教师（来自医学院、工程学院、人文科学学院和斯坦福直线加速器学院）参加了一次教师静修活动，开始了一个规划过程，该计划由两部分组成，旨在组织斯坦福大学生物计算研究生培训。首先，BMI学位课程的规模和范围将通过扩大研究议程来扩大，包括教师确定的六个战略领域：(1)结构和功能基因组学，(2)生物力学模拟，(3)计算机辅助干预和机器人技术，(4)图像采集和处理，(5)计算机辅助教学和网络教育，以及(6)信息学，数据建模和统计。其次，扩展后的BMI学位课程将作为一个焦点，将学科训练项目（如生物学、遗传学、计算机科学或机械工程）的学生整合到生物医学计算训练环境中。这些机制将包括创建跨学科课程，向技术研究生教授生物医学基础知识，并向生物医学研究生教授这些技术领域的基础知识。它还将包括旨在鼓励BMI和学科研究生之间知识转移的活动。因此，培训补助金将为BIM学生和学科学位研究生提供平均3年的资助，并为培养一支年轻、合格的科学家队伍提供机制，这些科学家有能力应对21世纪出现的科学挑战。

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.