Biostatistics in Genetics, Immunology and Neuroimaging (BGIN)

描述（由申请人提供）：我们建议继续我们现有的遗传学，免疫学和神经影像学（BGIN）生物统计学博士前培训计划。在本课程中，学生将学习如何在遗传学/基因组学、免疫学/疫苗学/传染病或神经影像学等领域进行统计和计算创新。埃默里大学这个项目的基本原理是在这些领域已经有了强大的跨学科研究项目，并且自BGIN项目开始以来，优势不断增加。埃默里大学的生物统计和生物信息系已经进入了一个快速增长的时期。我们目前正在招聘各个层次的新教师，重点是生物信息学和生物统计学之间的接口，特别是基因组学，高维分析，综合信息学，空间统计学，神经影像学，但任何领域都可以接受。我们非常有兴趣在我们系增加生物统计学博士前职位的数量。我们教师提供的研究经费和培训机会的数量已经远远超过了目前博士生的数量。基因表达阵列、蛋白质组学、代谢组学和测序等科学工具在免疫学和遗传学中都有应用。当加入神经成像领域时，所有的方法都代表了当前的科学前沿，并导致了庞大而复杂的数据结构，多重比较，可识别性，解释，错误发现率等问题。这些问题定义了培训下一代生物统计学家的工作平台。相关性（见说明）：拟议的培训计划提供遗传、免疫学和神经影像学研究中产生的生物医学数据定量分析的指导和经验。这些研究产生了大量的数据，需要新的方法以准确、可靠和可重复的方式总结、理解和报告研究结果。完成该课程的学员将有与现代临床、实验室和流行病学研究前沿的生物医学研究人员合作的经验，并将在快速发展的生物统计学和生物信息学领域担任领导角色。”

DESCRIPTION (provided by applicant): We propose a continuation to our existing predoctoral training program in Biostatistics in Genetics, Immunology, and Neuroimaging (BGIN). In this program, students learn to make statistical and computational innovations applied in the areas of genetics /genomics, immunology/ vaccinology / infectious diseases, or neuroimaging. The rationale for this program at Emory is the strong interdisciplinary research programs already in place in these areas, and increasing strengths added since the BGIN program began. The Department of Biostatistics and Bioinformatics at Emory has embarked in a period of rapid growth. We are currently advertising for new faculty at all levels, with a focus on the interface between bioinformatics and biostatistics, in particular, genomics, high-dimensional analysis, comprehensive informatics, spatial statistics, neuroimaging, but about any field would be acceptable. We have a great interest in increasing the number of biostatistics predoctoral positions in our department. Already, the number of research grants and training opportunities provided by our faculty far exceeds the current number of Ph.D. students. The scientific tools of gene expression arrays, proteomics, metabolomics, and sequencing are used in both immunology and genetics. When adding the field of neuroimaging, all approaches represent the current frontiers of science and result in large and complex data structures, problems of multiple comparisons, identifiability, interpretation, false discovery rates. These problems define the workbench for training the next generation of biostatisticians. RELEVANCE (See instructions): The proposed training program provides instruction and experience in the quantitative analysis of biomedical data arising from genetic, immunological, and neuroimaging studies. Such studies generate vast amounts of data and require new approaches to summarize, understand, and report findings in an accurate, reliable, and reproducible manner. Trainees completing the program will have experience collaborating with biomedical researchers at the forefront of modern clinical, laboratory, and epidemiologic research and will be positioned to take leading roles in the rapidly evolving fields of biostatistics and bioinformatics. '