MIT/Whitehead/Broad Computational Genetics Training Program

描述（由申请人提供）：我们提议建立一个新的计算遗传学跨学科研究培训计划，由麻省理工学院、怀特黑德研究所、麻省理工学院的布罗德研究所和哈佛大学共同努力。这个项目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一起开发新的算法、工具和方法来分析基因组和遗传数据，并以原则预测模型的形式表达这种分析。该计划的教员将包括5名麻省理工学院EECS和数学教员，4名怀特海学院教员，以及4名麻省理工学院和哈佛大学布罗德研究所的教员。该计划的主要研究学科包括：1)基于基因组学和遗传学实验和研究的数据分析的新方法和算法的发展；2)基于过去数据的研究原则设计方法；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和疾病有关的基因组、遗传和临床数据的方法的发展。

DESCRIPTION (provided by applicant): We propose to establish a new interdisciplinary research training program 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 interdisciplinary scientists, 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 explain complex 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 running a training program in this area for over seven years, and our students to date have made substantial contributions to 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 quantitative foundation 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. PUBLIC HEALTH REVELANCE - We will train scientists who can discover links between genetic information and risks for human disease. These studies can suggest appropriate therapies for certain diseases and give clues towards the development of new therapeutics. As more data form Genome Wide Association Studies becomes available, we expect that genetic information will become an important component of preventative medicine.