Predoctoral Training Program in Biological Data Science at Brown University

项目摘要(1页/30行)。 在这个大数据时代，建立一个成功的、独立资助的生物医学研究计划 需要熟练掌握生物数据(实验数据生成、生物信息学和统计推断) 以及与生命系统相关的理论(分析建模、计算模拟和进化论)。 这种二分法在博士培养中很难解决：生物专业的学生很少被训练来发展或 批评新的定量方法，定量分析生物数据的学生很少在 生物数据生成。迫切需要遏制应对这些挑战的零散努力，以及 相反，要建立一个集中的社区和培训计划，专注于培养生物数据科学家： 科学家的研究利用生物数据中观察到的模式来生成新的模型和 关于生物过程和系统的假说。 布朗大学生物数据科学博士前培训项目的目标是将 “i形”博士后学生--在一门学科上有实力--成为“pi形”生物数据科学家 有两个核心优势：(1)生成和分析生物数据，以及(2)开发理论模型 以及关于生物过程的可检验的假设。布朗大学的这个集中式社区将是 由28名在职、跨学科的教职导师负责，他们将指导NIH支持的四名博士前 每年的受训人员和4名布朗大学支持的受训人员(产生40个生物数据 5年以上的科学家)参加各种教学、研究和职业发展活动，为期一年。这些 活动将包括为期一年的新研究生研讨会、跨学科研究轮换、项目务虚会 为教师和实习生，以及一系列以职业发展为重点的圆桌讨论 跨学科的研究人员。由此产生的社区将促进基本技能的发展 跨学科的生物医学研究，包括向广泛和领域交流科学的能力- 特定受众，引导跨学科协作和拨款申请，学术和 以行业为基础的研究事业，并进行可重复和开放的科学。教导员的研究 项目涵盖了多种生物有机体、系统和问题，涉及进化遗传学， 功能基因组学、生物网络、衰老的分子生物学、发育稳健性、生物医学 信息学、免疫调节和生物物理学。此外，受训者有一个联合的年度 直接成本超过1200万美元的研究资金基础，为支持这一创新提供了坚实的基础 培训计划。这一培训计划将培养出具备对生活进行新见解的调查人员 来自复杂生物数据集的系统。

PROJECT SUMMARY (1 page/30 lines). In this era of Big Data, building a successful and independently funded biomedical research program requires fluency in both biological data (experimental data generation, bioinformatics, and statistical inference) and theory relevant to living systems (analytical modeling, computational simulation, and evolutionanry theory). This dichotomy is challenging to address in doctoral training: biology students are rarely trained to develop or critique new quantitative methods, and quantitative students analyzing biological data rarely gain depth in biological data generation. There is an urgent need to curb fragmented efforts to address these challenges, and to instead develop a centralized community and training program focused on fostering Biological Data Scientists: scientists whose research leverages observed patterns in biological data to generate new models and hypotheses for biological processes and systems. The objective of this Predoctoral Training Program in Biological Data Science at Brown University is to turn “I-shaped” predoctoral students — with strength in one discipline — into “pi-shaped” Biological Data Scientists with two core strengths: (1) generating and analyzing biological data, and (2) developing theoretical models for and testable hypotheses regarding biological processes. This centralized community at Brown University will be maintained by 28 engaged, crossdisciplinary faculty preceptors who will mentor four NIH-supported predoctoral trainees each year along with 4 Brown University-supported trainees each year (resulting in 40 Biological Data Scientists over 5 years) in a variety of didactic, research, and career development activities for one year. These activities will include a new year-long graduate seminar, crossdisciplinary research rotations, a program retreat for faculty and trainees, and a series of roundtable discussions focusing on professional development for interdisciplinary researchers. The resulting community will promote the development of skills essential for interdisciplinary biomedical research, including the ability to communicate science to both broad and field- specific audiences, navigate interdisciplinary collaboration and grant applications, interview for academic and industry-based research careers, and conduct reproducible and open science. The faculty preceptors' research programs cover multiple biological organisms, systems, and problems, ranging across evolutionary genetics, functional genomics, biological networks, molecular biology of aging, developmental robustness, biomedical informatics, regulation of immunity, and biological physics. Further, the preceptors have a combined annual research funding base of over $12 million in direct costs, offering a strong foundation to bolster this innovative training program. This training program will yield investigators equipped to extract new insights into living systems from complex biological datasets.