Quantitative Methods for HIV/AIDS Research

HIV/艾滋病研究的定量方法

• 批准号: 10700585
• 负责人: Cliburn C Chan
• 金额: $ 36.83万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-21 至 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10700585
• 关键词: Acquired Immunodeficiency Syndrome; Address; Area; Basic Science; Behavioral Sciences; Big Data; Bioinformatics; Biological; Biological Assay; Case Study; Clinical; Clinical Sciences; Collaborations; Communication; Communities; Competence; Complex; Computers; Consult; Consultations; Country; Data; Data Analyses; Data Science; Dedications; Development; Discipline; Educational process of instructing; Educational workshop; Engineering; Ensure; Environment; Faculty; Feedback; First Generation College Students; Foundational Skills; Future; Goals; Grant; HIV; HIV vaccine; HIV/AIDS; Institution; Interdisciplinary Study; Internships; Knowledge; Language; Learning Skill; Mentors; Mentorship; Methodology; Methods; North Carolina; Participant; Pilot Projects; Postdoctoral Fellow; Productivity; Recording of previous events; Reproducibility; Research; Research Personnel; Research Project Grants; Resource Development; Resources; Scholars Program; Science; Scientist; Series; Social Behavior; Structure; Talents; Testing; Training; Training Programs; Training and Education; Translational Research; Underrepresented Minority; Visualization; Work; bioinformatics pipeline; career; career development; computer science; data complexity; design; doctoral student; education research; experience; graduate student; high dimensionality; implementation science; interest; machine learning prediction; mathematical sciences; multidimensional data; multidisciplinary; novel; open data; peer; predictive modeling; programs; skills; statistics; summer internship; support network; training opportunity; vaccine development

Teams of HIV/AIDS biomedical researchers who perform their own data analysis and consult with biostatisticians as needed, are increasingly finding standard consultations inadequate because of the need to 1) tackle complex research questions, 2) make sense of big data, and 3) ensure that analysis is rigorous. There is a critical need to train the future HIV/AIDS workforce for an interdisciplinary big data environment in which quantitative experts with specialized methodological expertise are partnering on collaborative projects as appropriate. Researchers need to be trained to identify their own knowledge gaps and identify collaborators with the necessary expertise, which is getting more complex as quantitative expertise areas are becoming more and more specialized. To address this, the HIV/AIDS community needs to develop programs that train researchers and quantitative scientists — statisticians, computer scientists, mathematicians, engineers etc. — to work cohesively in team science. We propose a program to cross-train HIV/AIDS researchers in fundamental concepts of quantitative analysis, and quantitative scientists in the biological, clinical, and socio- behavioral context of HIV/AIDS research. This program capitalizes on the breadth and depth of resources in HIV/AIDS and in quantitative science at Duke to offer real-world HIV/AIDS research experiences with expert quantitative mentoring not only to Duke trainees, but also trainees from regional institutions in North Carolina who may not otherwise have access to these resources. It is designed to provide biomedical and quantitative trainees with the Skills, Opportunities, Access, and Resources (SOAR) for interdisciplinary HIV/AIDS team science. In the past project period, we taught data science, statistics, and assay bioinformatics to over 100 junior HIV/AIDS researchers through a series of 18 workshops we developed and implemented each year. We were also able to introduce 50 graduate students in statistics, mathematics, and computer science to multidisciplinary HIV/AIDS research through our summer internship program. To build upon this work, we are proposing a novel research education program designed to fulfill several key objectives: First, we will provide training for biomedical trainees interested in HIV/AIDS research to build up their skills in data science, predictive modeling, and assay analysis through a series of workshops centered on real-world HIV case studies. Second, we will implement a structured internship training program for quantitative graduate students to have an enhanced mentoring and team science experience working on real-world research problems with leading HIV/AIDS investigators. Third, we will develop a dedicated mentoring program for biomedical trainees and provide interdisciplinary professional development training opportunities, including long-term expert quantitative mentoring for trainees with data-driven research projects. This program will provide an exemplar for developing multidisciplinary team science training programs that can be used to develop the workforce across the country.

艾滋病毒/艾滋病的团队生物医学研究人员进行自己的数据分析并咨询 根据需要，生物统计学家越来越多地发现标准咨询不足 1）解决复杂的研究问题，2）弄清大数据，3）确保分析是严格的。 迫切需要培训未来的艾滋病毒/艾滋病劳动力，以实现跨学科的大数据环境 哪些具有专业方法论专家的定量专家正在合作合作作为合作项目 合适的。研究人员需要接受培训以识别自己的知识差距并确定合作者 有了必要的专业知识，随着定量专业知识领域的开始，这种专业知识变得越来越复杂 越来越专业。为了解决这个问题，艾滋病毒/艾滋病社区需要制定培训的计划 研究人员和定量科学家 - 统计学家，计算机科学家，数学家，工程师等 - 在团队科学中凝聚力工作。我们建议一项计划，以交叉培训艾滋病毒/艾滋病研究人员 定量分析的基本概念，以及生物，临床和社会学的定量科学家 艾滋病毒/艾滋病研究的行为环境。该计划利用了资源的广度和深度 杜克大学的艾滋病毒/艾滋病和定量科学专业的艾滋病毒科学，向专家提供现实世界中的艾滋病毒/艾滋病研究经验 不仅对杜克学员，而且对北卡罗来纳州地区机构的学员进行定量心理 谁可能无法访问这些资源。它旨在提供生物医学和定量 具有跨学科艾滋病毒/艾滋病团队的技能，机会，访问和资源（Soar）的学员 科学。在过去的项目时期，我们将数据科学，统计和测定生物信息学教授100多个 初级艾滋病毒/艾滋病研究人员通过我们每年开发和实施的18个研讨会。我们 还能够向50名统计，数学和计算机科学领域的研究生介绍 通过我们的暑期实习计划，多学科的艾滋病毒/艾滋病研究。为了建立这项工作，我们是 提出一项旨在实现几个关键目标的新型研究教育计划：首先，我们将提供 对对艾滋病毒/艾滋病研究感兴趣的生物医学学员的培训，以建立他们在数据科学领域的技能， 通过一系列以现实世界艾滋病毒为中心的研讨会进行预测建模和测定分析 研究。第二，我们将针对定量研究生实施结构化的实习培训计划 具有增强的心理和团队科学经验，从事现实世界研究问题的工作 领先的艾滋病毒/艾滋病研究人员。第三，我们将针对生物医学学员制定专门的心理计划 并提供跨学科的专业发展培训机会，包括长期专家 通过数据驱动的研究项目对学员的定量心理。该程序将提供一个典范 用于制定可用于发展劳动力的多学科团队科学培训计划 在全国范围内。