Hawaii Data Science Training for RCMI Researchers

项目摘要 毫无疑问，生物医学科学已经成为数据密集型科学。在过去的十年里， 新生物医学技术的蓬勃发展产生了大量的生物数据。这个庞大 数据包括各种类型的“组学”--数据、电子健康记录（EHR）数据、拍字节的成像等。 吧现在可以访问和挖掘大量的临床和表型数据。数据科学技能 涉及如何使用计算方法和算法来分析，管理和解释不同类型的 数据，并需要跨学科的知识，如生物医学领域的知识，计算 编程、统计和数学。少数民族机构研究中心（RCMI）资助的项目是 通常在少数民族机构进行，缺乏足够的数据科学技能和数据科学家专家来执行 数据密集型生物医学研究。因此，培训RCMI调查人员的数据科学技能至关重要。 位于太平洋中部，夏威夷的调查人员很难研究健康差异 前往美国大陆接受结构化数据科学培训和以项目为重点的分析支持 互动式培训。夏威夷的调查人员迫切需要当地的数据科学培训师。数据科学 在约翰A。夏威夷大学伯恩斯医学院（JABSOM）在训练数据方面有着丰富的经验 科学技能，以学生和不同层次的调查人员，以及支持他们的数据科学需求， 他们的研究项目。在该提案中，我们的目标是用下一代数据科学培训RCMI调查人员 skills.为实现这一目标，我们计划实现以下目标。目标1：提供教育和培训， RCMI研究人员及其合作者的数据科学相关技能。目标2：加强合作 RCMI资助的研究人员和数据科学家。除了培训RCMI调查人员及其合作者外， 在目标1的小组中，我们还将为研究人员提供个人数据科学培训，以促进合作 调查人员和我们的数据科学专家。

Project Summary There is little doubt that biomedical science has become data intensive science. In the last decade, we have witnessed the booming of new biomedical technologies generate massive amounts of bio-data. This massive data includes various types of “omics”-data, Electronic Health Record (EHR) data, petabytes of imaging, and so on. It is now feasible to access and mine the massive amount of clinical and phenotypic data. Data science skills involve how to use computational methods and algorithms to analyze, manage, and interpret different types of data, and require interdisciplinary knowledge such as biomedical domain knowledge, computational programming, statistics, and mathematics. Research Centers in Minority Institutions (RCMI) funded projects are often conducted in minority institutions and lack sufficient data science skills and data scientist experts to perform data intensive biomedical research. It is therefore essential to train data science skills for RCMI investigators. Located in the middle of the Pacific Ocean, it is difficult for Hawaii-based investigators studying health disparities to travel to the US continent to receive structured data science training and project-focused analytical support and interactive training. Hawaii investigators desperately need local data science trainers. The data science team at John A. Burns School of Medicine (JABSOM) University of Hawaii has rich experience in training data science skills to students and different levels of investigators, as well as supporting their data science needs in their research projects. In the proposal, we aim to train RCMI investigators with next generation data science skills. To reach the goal, we plan to accomplish the following aims. Aim 1: Provide education and training of data science-related skills to RCMI Researchers and their collaborators. Aim 2: Enhance collaborations between RCMI -funded researchers and data scientists. In addition to training RCMI investigators and their collaborators in a group in Aim 1, we will also offer individual data science training for investigators to foster collaborations between investigators and our data science experts.