Graduate Training in Computational and Systems Biology

项目摘要 目标是支持计算系统生物学培训计划（CSBTP），以培训学生 成为生物医学研究的领导者，在生物学，计算和工程的接口。这种努力是 以麻省理工学院的计算与系统生物学（CSB）跨学科博士前培训计划为中心， 这是麻省理工学院为对计算和系统生物学感兴趣的学生提供的主要培训项目， 是该领域唯一强调跨学科培训和研究的项目。课程教师是 集中在三个创始部门-生物工程（BE），生物学和电气 工程与计算机科学（EECS）-与其他部门的教师的额外参与。 培训教师的研究兴趣涵盖广泛的CSB相关领域，包括调控基因组学 和蛋白质组学，精准医学和医学基因组学，分子生物物理学和结构生物学， 生物网络和机器学习，以及癌症系统生物学。这项建议旨在扩大 培训师资队伍显著，包括7名教师在过去5年新聘请谁有积极的研究 外地的节目。学生直接申请CSB博士。从他们的本科或硕士课程 机构，并接受计算和系统生物学领域的多学科和跨学科培训。 该提案旨在为每年10个博士前培训项目提供资金，以延长研究轮换时间， 参与特殊项目活动。该方案的独特之处包括：（a）异常多样 跨科学和工程的研究领域的集合，具有高度协作的跨学科教师; (b)一个独特的跨学科课堂科目的核心，结合联合收割机生物，工程，统计和 （c）密集咨询和多学科论文委员会，以优化培训体验 为来自不同学术背景的学生举办;（d）每年举行一次有学生参加的务虚会， 教师专注于研究，职业和跨学科研究的挑战。

Project Summary The objective is to support a Computational Systems Biology training program (CSBTP) to train students to become leaders in biomedical research at the interface of biology, computation and engineering. The effort is centered in MIT's interdisciplinary predoctoral training program in Computational and Systems Biology (CSB), which is the primary training program at MIT for students interested in computational and systems biology and is the only program that emphasizes interdisciplinary training and research in the field. Program faculty are concentrated in the three founding departments – Biological Engineering (BE), Biology, and Electrical Engineering & Computer Science (EECS) – with additional involvement of faculty from other departments. Research interests of training faculty span a wide range of CSB-related areas, including Regulatory Genomics and Proteomics, Precision Medicine and Medical Genomics, Molecular Biophysics and Structural Biology, Biological Networks and Machine Learning, and Cancer Systems Biology. This proposal seeks to expand the pool of training faculty significantly, including 7 faculty newly hired in the past 5 years who have active research programs in the field. Students apply directly to the CSB Ph.D. program from their undergraduate or Master’s institution and receive multi- and inter-disciplinary training in the field of computational and systems biology. The proposal seeks funding for 10 predoctoral traineeships per year, enabling extended research rotations and participation in special program activities. Unique aspects of the program include: (a) unusually diverse collection of research areas across science and engineering, with highly collaborative interdisciplinary faculty; (b) a unique core of interdisciplinary classroom subjects that combine biology, engineering, statistics and computation; (c) intensive advising and multi-disciplinary thesis committees to optimize the training experience for students from diverse academic backgrounds; (d) an annual retreat with participation of students and faculty focusing on research, careers, and challenges to interdisciplinary research.