Hawaii Data Science Training for RCMI Researchers

夏威夷 RCMI 研究人员数据科学培训

• 批准号: 10452388
• 负责人: Jerris Robert Hedges
• 金额: $ 31.8万
• 依托单位: UNIVERSITY OF HAWAII AT MANOA
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-09-01 至 2022-09-19
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10452388
• 关键词: Artificial Intelligence; Bioinformatics; Biomedical Research; Biomedical Technology; Biometry; Burn injury; Cells; ChIP-seq; Clinical Data; Collaborations; Communities; Computational algorithm; Computing Methodologies; DNA sequencing; Data; Data Analyses; Data Science; Data Scientist; Data Set; Educational workshop; Electronic Health Record; Fostering; Funding; Goals; Hawaii; Health; Image; Individual; Instruction; Knowledge; Linux; Machine Learning; Mathematics; Methylation; Minority-Serving Institution; Pacific Ocean; Pythons; Research; Research Personnel; Research Project Grants; Research Training; Science; Scientist; Structure; Students; Training; Training and Education; Travel; Uncertainty; Universities; base; computer program; experience; graduate student; health disparity; investigator training; lectures; medical schools; microbiome; next generation; next generation sequencing; petabyte; phenotypic data; programs; skills; statistics; structured data; tool; training project; transcriptome sequencing

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.

项目总结