MIT EECS/Whitehead/Broad Training Program in Computational Biology(RMI)

描述（由申请人提供）：

DESCRIPTION (provided by applicant): We propose to establish a new interdisciplinary research training program in Computational Biology as a collaborative effort between MIT, the Whitehead Institute, and the Broad Institute. The goal of this program is to train computer science students to be effective interdisciplinary scientists, working as team members with biologists to develop new algorithms, tools, and approaches for analyzing experimental biological data and expressing this analysis in the form of principled predictive models. The program faculty will consist of five MIT EECS faculty in Computer Science, four MIT/Whitehead faculty members in Biology, and the head the MIT Broad Institute. The major research disciplines of this program include: the development of new approaches and algorithms for the analysis of data from biological experiments, approaches for the principled design of biological experiments based upon past data, the construction of computational models that explain complex biological phenomenon, and the development of approaches for interpreting clinical data relevant to human health and disease. It is proposed that four pre-doctoral trainees be supported in this program. We have been running an informal training program in this area for over three years, and our students to date have made substantial contributions to the field. Among our recent graduates are faculty at Stanford, Princeton, Duke, and CMU. Our pool of applicants is unusually strong, with 574 applicants in 2004 in the relevant sub-area 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 biology. In addition, we have run off-site interdisciplinary summer retreats for the past three years that have been very effective at catalyzing productive pre-doctoral research.