Core E: Data Sciences Core

核心 E：数据科学核心

• 批准号: 10085556
• 负责人: Hakmook Kang
• 金额: $ 24.91万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-06 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10085556
• 关键词: Academic Medical Centers; Address; Affect; Animal Model; Applications Grants; Award; Behavioral; Big Data; Bioinformatics; Biometry; Caregivers; Clinical; Collaborations; Complex; Consult; Consultations; Data; Data Analyses; Data Science; Data Science Core; Data Set; Databases; Disease; Down Syndrome; Electronic Health Record; Faculty; Funding; Future; Generations; Genetic; Goals; Grant; Health; Housing; Human Resources; Image; Individual; Institutes; Intellectual and Developmental Disabilities Research Centers; Intellectual functioning disability; Interdisciplinary Study; Link; Methodology; Methods; Modeling; Modernization; Outcome; Population; Psychology; Rare Diseases; Records; Reproducibility; Research; Research Design; Research Personnel; Research Project Grants; Resources; Role; Sample Size; Sampling; Services; Source; Statistical Data Interpretation; Statistical Methods; Statistical Models; Talents; Techniques; Testing; Training; Training Activity; Training Support; Universities; Work; autism spectrum disorder; biobehavior; bioimaging; complex data; data mining; data resource; disability; human model; improved; improved outcome; individualized medicine; informatics infrastructure; information processing; innovation; large datasets; large scale data; multimodal data; neuroimaging; neuroinformatics; neurophysiology; novel; patient oriented; programs; public health relevance; research and development; spatiotemporal; statistics; structured data; success; targeted treatment; tool; translational neuroscience

The success and impact of nearly every project in IDD hinges on the proper use of statistical techniques. Thus, Core E has a critical role in facilitating research for all IDDRC investigators, as well as for the progress of the other IDDRC Cores and Signature Research Project. Core E performs a unique function for IDDRC investigators as it helps them identify and use the statistical and methodological expertise and resources available at Vanderbilt University (VU) and Vanderbilt University Medical Center (VUMC) that are appropriate for their questions – especially for more complicated research designs (e.g., many layers of nesting) or those with statistical limitations (e.g., small sample sizes common in research with rare populations). Further, through generative activity with Clinical Translational and Translational Neuroscience Cores B and C, Core E provides sophisticated and non-trivial statistical methods and models tailored to IDD-related scientific questions (e.g., Bayesian spatio-temporal models for neuroimaging analysis). In addition to having considerable expertise in biostatistics, neuro-statistics, and quantitative psychology, Vanderbilt is also a national leader in developing big data structures and mining that data to advance health and development research, including the Synthetic Derivative (SD), a de-identified dataset of electronic health record data collected from over ~2.8 million total records. Though such big data structures are incredible resources to Vanderbilt, and especially IDDRC investigators with their ability to capture large samples of rare disorders, it can be challenging to put the data in analyzable formats and select suitable statistical approaches for analysis. Core E enables IDDRC investigators to fully capitalize on all these VU/VUMC resources through three aims: Aim 1, which provides access to modern statistical and data science methods to answer questions of relevance to IDD, including conducting data analyses for the Signature IDDRC Research Project; Aim 2, which enhances training in IDD research for those engaging in data science methods, including implementing a novel internal training grant program between Data Sciences Institute trainees and the IDDRC; and Aim 3, which supports innovation in health- related IDD research by facilitating use of large data sets such as the SD, including providing cutting-edge consultations and tools for working with large-scale SD IDD-curated database that IDDRC investigators can use for generating pilot data and conducting studies. Collectively, Core E’s aims and generative work and interactions with other IDDRC Cores not only meets the immediate needs of IDDRC investigators, but also anticipates future ones, by allowing for novel resources, platforms, and methods to be developed. By tackling and solving complex, multi-modal data science questions, Core E is poised to contribute substantially over the next 5 years to accelerating scientific discovery to improve the outcomes of people with IDDs.

IDD 中几乎每个项目的成功和影响都取决于统计技术的正确使用。 Core E 在促进所有 IDDRC 研究人员的研究以及促进该研究的进展方面发挥着至关重要的作用 其他 IDDRC 核心和签名研究项目 Core E 为 IDDRC 执行独特的功能。 研究人员，因为它可以帮助他们识别和使用统计和方法学专业知识和资源 范德比尔特大学 (VU) 和范德比尔特大学医学中心 (VUMC) 提供合适的服务 回答他们的问题——特别是对于更复杂的研究设计（例如，多层嵌套）或那些 具有统计限制（例如，在稀有人群的研究中常见的小样本）。 临床转化和转化神经科学核心 B 和 C、核心 E 提供生成活动 针对 IDD 相关科学问题（例如， 用于神经影像分析的贝叶斯时空模型）。 范德比尔特大学在生物统计学、神经统计学和定量心理学方面也处于全国领先地位。 数据结构和挖掘该数据以推进健康和发展研究，包括综合研究 Derivative (SD)，从超过 280 万个电子健康记录数据中收集的去识别化数据集 尽管这样的大数据结构对于 Vanderbilt，尤其是 IDDRC 来说是令人难以置信的资源。 由于研究人员有能力捕获罕见疾病的大量样本，因此将数据放入其中可能具有挑战性 IDDRC 调查人员可以使用可分析的格式并选择合适的统计方法进行分析。 通过三个目标充分利用所有这些 VU/VUMC 资源： 目标 1，提供访问 现代统计和数据科学方法来回答与 IDD 相关的问题，包括进行 IDDRC 标志性研究项目的数据分析；目标 2，加强 IDD 研究培训 那些从事数据科学方法的人，包括实施新颖的内部培训资助计划 数据科学研究所学员与 IDDRC 之间的合作；以及目标 3，支持健康领域的创新 通过促进 SD 等大型数据集的使用，包括提供前沿的 IDD 研究 IDDRC 调查人员可以使用用于使用由 SD IDD 管理的大型数据库的咨询和工具 用于生成试点数据和进行研究，以及 Core E 的目标和生成工作。 与其他 IDDRC 核心的交互不仅可以满足 IDDRC 调查人员的即时需求，还可以 通过允许开发新颖的资源、平台和方法来预测未来。 并解决复杂的多模态数据科学问题，Core E 有望做出重大贡献 未来 5 年加速科学发现，改善 IDD 患者的治疗效果。