Big Data Training for Cancer Research

癌症研究大数据培训

• 批准号: 10785775
• 负责人: MIN ZHANG
• 金额: $ 10.8万
• 依托单位: UNIVERSITY OF CALIFORNIA-IRVINE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10785775
• 关键词: 2019-nCoV; Acceleration; Address; Area; Big Data; Big Data to Knowledge; Bioinformatics; Biological; Biomedical Research; COVID-19; Case Study; Clinical; Clinical Data; Communication; Communities; Computers; Data; Data Analyses; Data Science; Data Scientist; Data Set; Dedications; Disease; Education; Educational process of instructing; Educational workshop; Faculty; Funding; Funding Opportunities; Goals; Growth; Hybrids; Immune; Immunologist; Immunology; Instruction; Knowledge; Literature; Machine Learning; Malignant Neoplasms; Mediating; Metagenomics; Motivation; Outcome; Participant; Persons; Physicians; Plasma; Positioning Attribute; Postdoctoral Fellow; Quality Control; Research; Research Personnel; Sampling; Scanning; Science; Scientist; Self Direction; Structure; Techniques; Time; Training; Training Programs; Translating; Translational Research; United States National Institutes of Health; Visualization; Work; anticancer research; biobank; biomedical scientist; clinical investigation; cohort; computer program; computer science; computerized tools; coronavirus disease; data integration; data to knowledge; data visualization; data wrangling; design; electronic health record system; empowerment; experience; graduate student; high throughput technology; instructor; interest; large scale data; literate; microbiome; novel; pandemic disease; precision medicine; programs; recruit; self-directed learning; skills; statistics; training opportunity

PROJECT SUMMARY Following the NIH Big Data to Knowledge (BD2K) initiative, we have been continuously funded by NCI to create a two-week summer training program for cancer researchers who are novices in big data analysis. During the past seven years, we have successfully organized both in-person and online hands-on training opportunities for traditionally trained biomedical and cancer researchers. Our current workshop uses applications involving cancer data to teach valuable data science and bioinformatics approaches. However, we strongly believe that these data science skills are somewhat general. With this funding opportunity, we are excited to extend our workshop materials with an additional module utilizing data familiar to infectious and immune-mediated disease (IID) researchers and relevant approaches such as scripting in R, exploratory analysis, data wrangling, and visualization of longitudinal data. The proposed supplement is directly responsive to NOT-AI-23-010 and will enable IID researchers to more confidently explore existing IID data, set up their own analysis plans, and communicate within research teams. Our proposed supplement course has three goals: (1) Develop two new IID-related case studies for teaching purposes, both relevant to IID researchers and a more general audience of biomedical researchers; (2) Create publicly accessible, reusable online materials for IID and cancer research communities that provide instruction in exploratory data analysis, data wrangling, quality control, and computer programming; and (3) Add these new case studies and materials to supplement the currently funded workshop on big cancer data as a new hybrid (in- person and online) pre-module. Like our original R25 workshop, this course will target graduate students, postdoctoral trainees, physician-scientists, and biomedical scientists, with strong IID backgrounds yet limited advanced coursework in statistics, bioinformatics, and computer science. We plan to offer this new module as an addition to our current course rather than as a separate course. Even a brief scan of the current literature will provide evidence between cancer, immunology (including COVID), and microbiome. We expect additional benefits for participants based on interdisciplinary interactions and knowledge they will obtain through participation in the combined course. Finally, many participants in past courses state that having dedicated time to interact with faculty and other participants and to explore topics of interest independently gave them the confidence to ask and answer questions—in essence to be self-directed learners.

项目概要 继 NIH 大数据知识化 (BD2K) 计划之后，我们不断得到 NCI 的资助来创建 针对大数据分析新手的癌症研究人员的为期两周的夏季培训计划。期间 在过去的七年里，我们成功地为学生组织了现场和在线实践培训机会 传统上训练有素的生物医学和癌症研究人员。我们当前的研讨会使用涉及癌症的应用程序 数据来教授有价值的数据科学和生物信息学方法。然而，我们坚信，这些 数据科学技能有些一般。有了这个资助机会，我们很高兴能够扩大我们的研讨会 具有附加模块的材料，利用熟悉传染病和免疫介导疾病 (IID) 的数据 研究人员和相关方法，例如 R 脚本、探索性分析、数据整理等 纵向数据的可视化。拟议的补充直接响应 NOT-AI-23-010，并将 使 IID 研究人员能够更加自信地探索现有 IID 数据、制定自己的分析计划，以及 研究团队内的沟通。 我们提出的补充课程有三个目标：(1) 开发两个新的 IID 相关教学案例研究 与 IID 研究人员和更广泛的生物医学研究人员相关的目的； (2)创建 可公开访问、可重复使用的在线材料，为 IID 和癌症研究社区提供指导 探索性数据分析、数据整理、质量控制和计算机编程； (3) 添加这些新的 案例研究和材料，以补充目前资助的关于癌症大数据作为新混合体的研讨会（in- 个人和在线）预模块。与我们最初的 R25 研讨会一样，本课程将针对研究生， 博士后实习生、医师科学家和生物医学科学家，具有强大的 IID 背景但数量有限 统计学、生物信息学和计算机科学的高级课程。 我们计划提供这个新模块作为我们当前课程的补充，而不是作为单独的课程。甚至一个 对当前文献的简要浏览将提供癌症、免疫学（包括新冠病毒）和 微生物组。我们期望基于跨学科的互动和知识为参与者带来额外的好处 他们将通过参加联合课程获得。最后，过去课程的许多参与者表示 有专门的时间与教师和其他参与者互动并独立探索感兴趣的主题 让他们有信心提出和回答问题——本质上是成为自主学习者。