Biostatistics Training for Basic Biomedical Research

描述(申请人提供)：人类基因组测序为生物学的下一个主要前沿--蛋白质组奠定了基础，并为生物医学研究的新“组学”时代铺平了道路。数据的爆炸性级联需要集成生物信息学工具来表示和处理数据，以及复杂的统计和数学方法来验证、分析、建模，最后统一和解释无数的“基因组”数据，以推断生物功能。南卡罗来纳医科大学(MUSC)生物统计、生物信息学和流行病学系提出的基础生物医学研究生物统计培训(BTBBR)计划的目的是培养在基础生物医学科学方面拥有丰富教学和实践经验的新一代生物统计学家，以便他们准备好在新一代基础生物医学研究中扮演关键角色。BTBBR计划强调生物统计学理论和方法的整合，包括非线性系统分析和数学建模，以及生物信息学的工具，以解决现代多学科生物学研究中的定量前沿。该计划将利用一个成熟和成功的大学范围的计划，该计划提供一个共同的基础科学课程，提供入门级基础生物医学科学的有组织的、基础广泛的教学和实验室培训；一个现有的生物统计学计划，强调生物知识和生物统计学原理的整合；以及基础生物医学科学研究人员在MUSC具有国家公认优势的四个重点领域--蛋白质组学、脂质组学、信号和神经生物学--承认需要生物统计学投入的氛围。

DESCRIPTION (provided by applicant): The sequencing of the human genome has set the stage for the next major frontier in biology, the proteome, and has paved the way for the new "omics" era in biomedical research. The exploding cascade of data requires integration of bioinformatics tools for data representation and manipulation and sophisticated statistical and mathematical approaches for validating, analyzing, modeling and, finally, unifying and interpreting the myriad of "omic" data to infer biological function. The aim of the Biostatistics Training for Basic Biomedical Research (BTBBR) program, proposed by the Department of Biostatistics, Bioinformatics, and Epidemiology at the Medical University of South Carolina (MUSC), is to train a new generation of biostatisticians who have substantial didactic and hands-on experience in the basic biomedical sciences so that they are prepared to assume key roles in this new generation of basic biomedical research. The BTBBR program stresses the integration of biostatistical theory and methods, including nonlinear systems analysis and mathematical modeling, with tools from bioinformatics to address quantitative frontiers in modern multi-disciplinary biological research. The program will capitalize on an established and successful college-wide program offering a common basic science curriculum that provides structured, broad-based didactic and laboratory training in the basic biomedical sciences at an entry level; an established biostatistics program that emphasizes integration of biological knowledge and biostatistical principles; and an atmosphere of acknowledged need for biostatistical input among basic biomedical science researchers in four focus areas in which MUSC has nationally recognized strength: proteomics, lidipomics, signaling, and neurobiology.