Statistical Genomics and Systems Biology Workshop

描述(由申请人提供)：人类基因组计划及其分支极大地增加了研究人员可用的遗传数据量。将生物学家和量化科学家聚集在一起的跨学科研究对于挖掘海量公共数据和了解人类疾病和变异的遗传基础至关重要。新的定量方法彻底改变了高维基因组数据集的分析。我们有超过18年由美国国立卫生研究院资助的开发这些前沿方法的经验，并有超过10年的经验在密集的夏季研讨会上向遗传学研究人员教授这些方法。我们的持续目标是创建工具和研讨会，培训下一代基因组科学家挖掘、分析和共享数据，这将促进对疾病的理解、诊断和治疗，并促进公共健康。作为这一教育努力的一部分，我们建议提供一个为期一周的密集研讨会，内容是统计基因组学和系统生物学的理论和实践(重点是网络方法)。参与者将花费大量时间进行动手练习，使用我们团队为发现影响疾病特征的基因而开发的广泛使用的最先进的应用程序。我们将使用真实和模拟的数据集，这些数据集将从经典的链接和 关联测试用于分析高密度SNP基因类型、RNA-seq转录本计数、来自深度测序的稀有变异以及网络分析方法。参与者将从研究生到高级研究人员，包括定量和非定量的，来自许多领域，包括生物学、遗传学、临床和生物医学研究、跨学科和翻译科学、生物信息学、统计学、计算生物学、计算机科学、应用数学、物理和社会科学。我们计划将定量、生物学和跨学科的研究人员聚集在一起，让他们了解定量基因组学的问题和词汇，以便他们能够有效和富有成效地进行交流和合作。如果没有定量和定性科学家之间的理解和密切合作，我们将无法解决现代基因组学的挑战。研讨会将在加州大学洛杉矶分校的校园内举行，所有材料也将通过我们的远程学习计划远程提供。在接下来的几年里，重点将在统计基因组学和系统生物学之间交替，但每年都会讨论这两个主题。每年的重点主题将在一个为期五天的强化课程中涵盖，其中包括计算机练习。次要主题将在主要主题之前或之后的一个为期两天的选修模块中涵盖。所有课程材料，加上额外的资源，将在全年向课程校友和任何感兴趣的研究人员开放。在远程学习环境中，还将全年提供与课程讲师的反馈和互动。

DESCRIPTION (provided by applicant): The human genome project and its offshoots have dramatically increased the amount of genetic data available to researchers. Interdisciplinary studies that bring together biologists and quantitative scientists are critical to mine the vast amount of public data and understand the genetic basis of human disease and variation. New quantitative methods have revolutionized the analysis of high dimensional genomic data sets. We have over 18 years of NIH-funded experience developing these leading-edge methods, and over ten years experience teaching these methods to genetic researchers in intensive summer workshops. Our continuing goal is to create tools and workshops to train the next generation of genomic scientists to mine, analyze, and share data, which will advance the understanding, diagnosis, and treatment of disease, and promote public health. As part of this educational endeavor, we propose to offer an intensive week-long workshop in the theory and practice of statistical genomics and systems biology (with an emphasis on network methods). The participants will spend much of their time performing hands-on exercises with widely used, state-of-the-art applications our group has developed for discovering genes that influence disease traits. We will use real and simulated data sets that will journey from classic linkage and association tests to the analysis of high-density SNP genotypes, RNA-seq transcript counts, rare variants from deep sequencing, and network analysis methods,. The participants will range from graduate students to senior researchers, both quantitative and non-quantitative, and from many fields, including biology, genetics, clinical and biomedical research, interdisciplinary and translational sciences, bioinformatics, statistics, computational biology, computer science, applied mathematics, physics, and social science. We plan to bring together quantitative, biological, and interdisciplinary researchers and give them an understanding of the issues and the vocabulary of quantitative genomics so that they can communicate and collaborate effectively and productively. Without understanding and close collaboration between quantitative and qualitative scientists, solutions to the challenges of modern genomics will elude us. The workshops will be offered on the campus of the University of California, Los Angeles, and all materials will also be offered remotely, through our Distance Learning Initiative. In successive years the emphasis will alternate between statistical genomics and systems biology, but each year both topics will be addressed. The focal topic each year will be covered in an intensive five-day course, with computer exercises. The secondary topic will be covered in an optional two-day module either before or after the primary topic. All course materials, plus additional resources, will be available throughout the year to course alumni and any interested researcher. Feedback and interaction with the course instructors will also be available throughout the year in the Distance Learning environment.