Biomedical Data Science Innovation Labs: An Intensive Research Project Development Program

生物医学数据科学创新实验室：密集研究项目开发计划

• 批准号: 10264799
• 负责人: John Darrell Van Horn
• 金额: $ 48.58万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-16 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10264799
• 关键词: Address; Applications Grants; Area; Biological; Biomedical Research; Biophysics; Career Choice; Clinical; Collaborations; Communities; Computers; Data; Data Analytics; Data Science; Dedications; Dependence; Development; Discipline; Disease; Education Projects; Educational workshop; Engineering; Ensure; Epidemiology; Evaluation; Event; Exposure to; Faculty; Feedback; Foundations; Funding; Funding Agency; Funding Mechanisms; Generations; Goals; Grant; Health; Human; Immersion; Knowledge; Leadership; Learning; Logistics; Mathematics; Measures; Mentors; Mentorship; Methods; Modeling; Modernization; Outcome; Participant; Persons; Physics; Postdoctoral Fellow; Privatization; Process; Program Development; Questionnaires; Reproducibility; Research; Research Personnel; Research Project Grants; Research Proposals; Research Training; Science; Scientist; Senior Scientist; Series; Social Network; Source; Supervision; System; Thinking; Time; Training; Training Activity; Training and Education; United States National Institutes of Health; Use Effectiveness; Vision; Visualization; Woman; analytical method; base; big biomedical data; biomedical data science; career; community building; computer science; data modeling; faculty mentor; follow-up; innovation; interest; large scale data; mathematical model; mathematical sciences; member; mid-career faculty; multidisciplinary; next generation; novel; outreach; program dissemination; programs; public health relevance; responsible research conduct; science education; senior faculty; skills; skills training; statistics; success; tenure track; tool; trend; virtual; visual media; web site; website development

Abstract: This IPERT R25 application will formalize and expand upon a series of unique Biomedical Data Science Innovation Lab online and in-person workshops whose immersive and hands-on approach will accelerate the ability of early-career biomedical and quantitative investigators to form new collaborations around biomedical science projects. Each year a distinct biomedical topic will be specifically identified which would benefit from a fresh or divergent data science perspective. During the Biomedical Data Science Innovation Lab events, professional facilitators and senior scientist mentors (with relevant expertise and exposure to the topic area) assist the participants - guiding the development of innovative research project proposals. The primary purpose of the facilitators is to build the community, strengthen the bonds between the participants, and help the teams to form. Program directorship will provide leadership, continuity, and logistical support, while other stakeholders provide vision, expertise, and ongoing program feedback. Senior faculty mentors will contribute topic background and data science applications while also providing oversight and feedback on the development of new projects. Early-career investigators (at the post-doc, assistant to newly associate professor level, research and tenure track) from quantitative (including but not limited to applied and/or theoretical mathematics, statistics, computer science, physics, and engineering) and biomedical fields (including but not limited to biological, biophysical, epidemiological, and clinical disciplines) will be welcomed to submit applications. A broad diversity of backgrounds is desired with women and members of underrepresented communities encouraged to apply. Throughout the year-long program, participants will benefit directly from explicit skills training in data science methods, reproducibility, Team Science, responsible conduct in research, and will learn about research funding mechanisms directly through interaction with NIH and NSF program officers. Participants will form multidisciplinary teams during the in-person workshop to develop biomedical topic domain projects involving mathematical modeling, statistical analytics, and other quantitative methods. Upon completion of the workshops, follow-up virtual activities will solidify teams and their research proposals as grant applications suitable for submission to federal and private funding agencies. Rigorous assessment and characterization of skills training activities as well as team effectiveness using emerging Science of Team Science-based approaches will strictly pursued. A rich program for dissemination of workshop activities includes broad-based outreach, a detailed website, and the development of professional-grade visual media and materials. With a well-suited team and a track record of prior success, this is a novel program for research community building, fully aligned with the goals of the IPERT R25 program. 1

摘要： 该IPERT R25应用程序将正式化并扩展一系列独特的生物医学数据科学 创新实验室在线和现场研讨会，其沉浸式和实践方法将加速 早期职业生物医学和定量研究人员围绕生物医学形成新合作的能力 科学项目。每年将具体确定一个独特的生物医学主题， 新的或不同的数据科学观点。在生物医学数据科学创新实验室活动期间， 专业主持人和资深科学家导师（具有相关专业知识和对专题领域的了解） 协助参与者-指导创新研究项目提案的开发。主要目的 促进者的任务是建立社区，加强参与者之间的联系，并帮助团队 形成。项目主管将提供领导、连续性和后勤支持，而其他利益相关者将提供支持。 提供愿景、专业知识和持续的计划反馈。资深教师导师将贡献主题背景 和数据科学应用，同时还对新项目的开发提供监督和反馈。 早期职业研究人员（博士后、新副教授助理、研究和终身教职） 轨道）从定量（包括但不限于应用和/或理论数学，统计学，计算机 科学、物理学和工程学）和生物医学领域（包括但不限于生物学，生物物理学， 流行病学及临床学科）递交申请。广泛多样的 背景是可取的，鼓励妇女和代表性不足的社区成员申请。 在整个为期一年的计划中，参与者将直接受益于数据科学的明确技能培训 方法，可重复性，团队科学，负责任的研究行为，并将了解研究资金 直接通过与NIH和NSF项目官员的互动机制。参与者将形成 多学科团队在现场研讨会期间开发生物医学主题领域项目， 数学建模、统计分析和其他定量方法。讲习班结束后， 后续的虚拟活动将巩固团队和他们的研究提案，作为适合于 提交给联邦和私人资助机构。严格评估和描述技能培训 活动以及团队的有效性使用新兴的科学团队科学为基础的方法将严格 追求。一个丰富的计划，以传播讲习班的活动，包括广泛的宣传，详细的 网站，并开发专业级的视觉媒体和材料。有一个很好的团队， 这是一个建立研究共同体的新计划，完全符合目标 IPERT R25计划的一部分。 1