BIOINFORMATIC and COMPUTATIONAL BIOLOGY TRAINING PROGRAM

描述(由申请者提供)：我们为生物信息学、基因组技术和计算生物学的博士生设计了一个培训计划。 一旦现代生物学变得越来越依赖定量方法，就出现了几种训练方法，主要是作为一种必要的问题，而不是计划。其中一些人的特点是教授一个领域的专家另一个领域的能力，当该领域正在迅速变化，以便在一个尚未明确的全新领域培训一支新的研究人员队伍时，其中一些非常重要。这项活动仍然重要，但已不再足够。在传统学术数学系中工作的数学家将继续学习生物学，并为其发展做出贡献。实验室生物学家将同样获得利用基因组技术所需的统计和计算技术方面的能力。但我们相信三件关键的事情：1)在该领域做出最大贡献的将是受过计算生物学本身培训的新一代研究人员；2)开始这样一种培训努力的时候已经到来，大量非常聪明的本科生积极主动地攻读数学和生物科学或类似的跨学科教育的双专业；3)可能比其他两种更具争议性，数学天赋相对较少，数学培训需要学生和教师付出大量努力。因此，我们的计划建立在统计学和计算机科学的坚实基础上，同时提供与实验生物学实验室、临床研究计划和生命科学文化的直接整合。

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.