Interdisciplinary training: Statistical Genetics/Genomics & Computational Biology

 描述（申请人提供）：这是哈佛公共卫生学院（HSPH）统计遗传学/基因组学和计算生物学跨学科培训项目的续签申请。受训人员将是生物统计学和流行病学系HSPH的博士预科生，这两个系将共同管理赠款。该计划建议支持7名博士前学生。该计划的目标是培养下一代定量基因组科学家对统计遗传学/基因组学和生物信息学/计算生物学的前沿方法和合作研究有很强的理解和承诺，并应用于遗传流行病学，分子生物学和基因组医学。我们致力于培养学员成为未来的定量领导者，开发和应用先进的，可扩展的统计和计算方法来管理，分析，整合和解释基础科学，流行病学和临床研究中的大量遗传和基因组数据，促进跨学科研究，并与遗传和基因组研究的主题科学家进行有效的沟通和合作。在这次更新中，我们将扩大培训计划的范围，以加强大组学数据科学和可重复研究的定量培训。培训计划涉及由完成和经验丰富的多学科教师，包括生物统计学家，生物信息学家和计算生物学家，遗传流行病学家和分子生物学家的积极参与。它结合了课程训练的元素，在生物科学的“湿”实验室和生物统计学的“干”实验室的实验室轮换， 计算生物学和遗传流行病学，指导方法和协作研究，以及在刺激和培养跨学科环境中的丰富职业发展机会，这将使毕业生成为领先的定量基因组科学家。

 DESCRIPTION (provided by applicant): This is a renewal application of the Interdisciplinary Training Program in Statistical Genetics/Genomics and Computational Biology at the Harvard School of Public Health (HSPH). Trainees will be pre-doctoral students at HSPH in the Departments of Biostatistics and Epidemiology, which will jointly administer the grant. The program proposes support for seven pre-doctoral students. The goal of the program is to train the next generation of quantitative genomic scientists to have a strong understanding of, and commitment to, cutting- edge methodological and collaborative research in statistical genetics/genomics and bioinformatics/computational biology with applications in genetic epidemiology, molecular biology and genomic medicine. We are committed to train trainees to become future quantitative leaders to develop and apply advanced, scalable statistical and computational methods to manage, analyze, integrate, and interpret massive genetic and genomic data in basic science, epidemiological and clinical studies, to promote interdisciplinary research, and to effectively communicate and collaborate with subject-matter scientists in genetic and genomic research. In this renewal, we will expand the scope of the training program to enhance quantitative training in big `omics data science and reproducible research. The training program involves active participation by accomplished and experienced multidisciplinary faculty members, including biostatisticians, bioinformaticians and computational biologists, genetic epidemiologists, and molecular biologists. It combines elements of training in coursework, lab rotations in both "wet" labs in biological science and "dry" labs in biostatistics, computational biology, and genetic epidemiology, directed methodological and collaborative research, and rich career development opportunities in a stimulating and nurturing interdisciplinary environment, that will prepare graduates to become leading quantitative genomic scientists.