CF Bioinformatics and Biostatistics Core

本申请的首要目标是继续发展达特茅斯囊性纤维化研究 中心（DartCF），建立在我们强大的CF相关研究的历史，并扩大我们的能力， 研究肠道中宿主-微生物的相互作用及其对肠道生态失调和整体系统健康的影响 与CF相关的糖尿病患者。囊性纤维化生物信息学的主要目标， 生物统计学核心（CF-BBC）是提供专家级的生物信息学和生物统计学支持和培训。 国家的最先进的生物信息学和生物统计学已成为必不可少的生物医学研究一般， 特别是CF研究，因为越来越复杂的实验设计和大数据集， 来自基因组学、转录组学、蛋白质组学和相关的高维技术。我们发现CF 受过生物信息学和生物统计学培训的研究人员比其他工作人员更有能力分析自己的数据 在通用数据分析核心设施，CF研究人员分享他们所学到的与他人在他们的 领域因此，投资生物信息学和生物统计学培训是对以下问题的有效且高效的应对措施 与CF相关的科学数据数量迅速增加。我们已经成功培训了四名CF科学家， 现在作为教师参加我们的教育计划，还有几十个人报告说，他们是 在非正式的基础上与CF研究人员分享他们在生物信息学和生物统计学方面的培训。重要的是， 我们举办两个强化课程，提供应用技术和统计基础方面的培训。 生物信息学，我们的教学系统包括每周会议（R俱乐部）和研讨会，学生 和教师介绍他们的经验，使用统计，图形和信息学工具。这些每周例会 部分由CF研究社区的参与者设计，使我们的教育议程保持同步 不断发展的研究需求。我们提供生物信息学支持的模式也是创新的，因为CF- 英国广播公司的生物信息学和生物统计学专家是训练有素的CF研究人员。这极大地提高 沟通，使核心在实验设计，理解生物学等领域更有价值。 研究结果的意义、建议后续实验、撰写论文和与审稿人沟通 评论.最后，CF-BBC在致力于开放科学方面具有创新性。我们的核心帮助DartCF 社区格式化和注释数据，并将其存款在适当的数据库中，使我们的数据更容易找到， 可访问、可互操作和可重用（FAIR）。我们还帮助DartCF研究人员查找、下载和 重新分析与他们的研究相关的公共数据集，使他们能够产生新的假设，并确保 初步调查结果是可重复的总之，CF-BBC的使命是提供专家级的 生物信息学和生物统计学的支持和培训DartCF教师和学员，以及我们的合作伙伴 机构，并支持和加强开放科学。

The overarching goal of this application is to continue to develop the Dartmouth Cystic Fibrosis Research Center (DartCF), building on our strong history of CF-related research and expanding our capability to investigate host-microbe interactions in the gut, and their impact on gut dysbiosis and overall systemic health of patients with CF-related diabetes. The primary objective of the Cystic Fibrosis Bioinformatics and Biostatistics Core (CF-BBC) is to provide expert-level bioinformatics and biostatistical support and training. State-of-the-art bioinformatics and biostatistics have become essential in biomedical research in general, and CF research in particular, because of increasingly complex experimental designs and the large data sets that arise from genomic, transcriptomic, proteomic and related high-dimension techniques. We have found that CF researchers trained in bioinformatics and biostatistics are better positioned to analyze their own data than staff at generic data analysis Core facilities, and that CF researchers share what they’ve learned with others in their field. Therefore, investing in bioinformatics and biostatistics training is an effective and efficient response to rapidly increasing amounts of CF related scientific data. We have successfully trained four CF scientists who are now participating as instructors in our educational programs, and dozens more who report that they are sharing their training in bioinformatics and biostatistics with CF researchers on an informal basis. Importantly, we host two intensive courses to provide training in the technical and statistical foundations of applied bioinformatics, and our instructional system includes weekly meetings (R Club) and seminars at which students and faculty present their experience using statistical, graphical, and informatics tools. These weekly meetings are designed in part by participants from the CF research community, keeping our educational agenda in sync with evolving research needs. Our model of providing bioinformatics support is also innovative because CF- BBC bioinformatics and biostatistics specialists are trained CF researchers. This greatly improves communication and makes the Core more valuable in areas like experimental design, understanding biological meaning of results, suggesting follow up experiments, writing manuscripts and dealing with reviewer comments. Finally, the CF-BBC is innovative in its commitment to Open Science. Our Core helps the DartCF community format and annotate data, and deposit it in appropriate databases, making our data more findable, accessible, interoperable and reusable (FAIR) by others. We also help DartCF researchers find, download and reanalyze public data sets relevant to their research, allowing them to generate new hypotheses and ensure that preliminary findings are reproducible. In summary, the mission of the CF-BBC is to provide expert-level bioinformatics and biostatistical support and training to DartCF faculty and trainees, and our partnering institutions, and to support and enhance Open Science.