MIT/Whitehead/Broad Computational Genetics Training Program

请参阅说明)： 我们建议在计算遗传学中建立一个新的跨学科研究培训计划作为一个合作 麻省理工学院、怀特黑德研究所、麻省理工学院博德学院和哈佛大学之间的合作。这项计划的目标是 培养麻省理工学院的学生成为有效的跨学科科学家，作为团队成员与生物学家合作开发新的 用于分析基因组和遗传数据并将这种分析表示为 有原则的预测模型。该计划的教员将由五名麻省理工学院EEC和四名数学教员组成 怀特黑德的教职员工，以及麻省理工学院和哈佛大学博德学院的四名成员。主要研究成果 该计划的学科包括：1)开发新的方法和算法来分析来自 基于基因组学和遗传学的实验和研究；2)研究的原则性设计方法 过去的数据；3)构建解释复杂表型和生物现象的计算模型；4) 以及解释与人类健康相关的基因组、遗传和临床数据的方法的发展 疾病。 本方案拟向4名博士前实习生提供支助，每人为期两年(共8名 插槽)。我们已经在这一领域开展了七年多的培训计划，到目前为止，我们的学生已经取得了 对这一领域做出了重大贡献。我们最近毕业的学生中有斯坦福大学伯克利分校的教员。的 华盛顿大学、普林斯顿大学、杜克大学和芝加哥大学。我们的申请者非常强大，2008年有592名申请者 计算机科学的相关子领域。在我们建议的研究培训计划中，学员将拥有非常严格的 麻省理工学院计算机科学研究生项目的技术和定量基础，结合形式 跨学科的课程工作和计算机科学与生物学院之间的共同导师安排 成员。我们的博士前学生具有很强的技术能力，这为 在计算遗传学中开创突破性的新方法和新算法。

See instructions): We propose to establish a new interdisciplinaryresearch trainingprogram in Computational Genetics as a collaborative effort between MIT, the Whitehead Institute, and the Broad Institute of MIT and Harvard. The goal of this program is to train MIT students to be effective interdisciplinaryscientists, working as team members with biologists to develop new algorithms, tools, and approaches for analyzing genomic and genetic data and expressing this analysis in the form of principled predictive models. The program faculty will consist of five MIT EECS and Mathematics faculty, four Whitehead faculty members, and four members of the Broad Institute of MIT and Harvard. The major research disciplines of this program include: 1) the development of new approaches and algorithms for the analysis of data from genomics and genetics based experiments and studies; 2) approaches for the principled design of studies based upon past data; 3) the construction of computational models that explaincomplex phenotypes and biological phenomenon; 4) and the development of approaches for interpreting genomic, genetic, and clinical data relevant to human health and disease. It is proposed that four pre-doctoral trainees be supported in this program, each for a period of two years (a total of 8 slots). We have been runninga training program in this area for over seven years, and our students to date have made substantial contributionsto the field. Among our recent graduates are faculty at Stanford, Berkeley, Univ. of Washington, Princeton, Duke, and CMU. Our pool of applicants is unusually strong, with 592 applicants in 2008 in relevant sub-areas of Computer Science. Trainees in our proposed research training program will have a very rigorous technical and quantitativefoundation from the MIT graduate program in Computer Science, combined formal interdisciplinary course work and a co mentorship arrangement between a Computer Science and a Biology faculty member. The strong technical skills present in our pre doctoral students have provided an excellent foundation for the creation of ground breaking new approaches and algorithms in Computational Genetics.