Design and Analysis Core

设计与分析核心

• 批准号: 10246485
• 负责人: Zhijin Jean Wu
• 金额: $ 32.45万
• 依托单位: BROWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-15 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10246485
• 关键词: Behavior; Behavioral; Biometry; Biostatistics Core; Center for Translational Science Activities; Centers of Research Excellence; Characteristics; Clinical Research; Collaborations; Collection; Communities; Computational Biology; Computer software; Computers; Data; Data Analyses; Data Science; Data Scientist; Development; Ensure; Environment; Experimental Designs; Faculty; Fostering; Functional Magnetic Resonance Imaging; Funding; Goals; High Performance Computing; Hospitals; Infrastructure; Institution; Interdisciplinary Study; Joints; Learning; Machine Learning; Methodology; Methods; Mission; Modeling; Motivation; Nervous System Physiology; Neuraxis; Neurosciences; Neurosciences Research; Performance; Phase; Process; Psychologist; Publications; Reproducibility; Research; Research Design; Research Personnel; Resources; Rhode Island; Science; Scientist; Services; Solid; Statistical Data Interpretation; Statistical Methods; Statistical Models; System; Technology; Training; Translational Research; Universities; Validation; Visualization; Work; analytical method; analytical tool; biomedical informatics; complex data; computational neuroscience; computer science; data acquisition; data management; design; experimental study; follow-up; frontier; grasp; high standard; human disease; innovation; machine learning method; magnetic resonance imaging/electroencephalography; member; neuroimaging; novel; response; science and society; statistical and machine learning; statistical center; statistics; tool; training opportunity; training project

The mission of the Design and Analysis Core (DAC) is to provide faculty-level support for neuroscience research in principled study design, statistical modeling, inference, machine learning and high performance computation. The DAC is complementary to but distinct from the Behavior and Neuroimaging Core (BNC), with the BNC providing practical, implementation services. The DAC has the following Specific Aims in the Phase II: (1) Provide project-specific, faculty-level collaboration to COBRE Project Leaders (PLs) on design and analysis; (2) Develop novel statistical methodology and computing toolboxes for study design and comprehensive analysis of neuroimaging and behavioral data; (3) Coordinate and facilitate access to the Brown University central computing and information infrastructure and provide complementary support on data management; (4) Serve as a locus for training and exchange of ideas on computational neuroscience and extend the statistical and computational support to the growing community of neuroscience researchers in Rhode Island. The DAC consists of four faculty members from the Departments of Biostatistics and Computer Science, and two staff scientists, one shared with the BNC. The DAC will support the COBRE Projects by matching faculty expertise to specific scientific goals, by guiding experimental design, identifying adequate statistical and computational approaches and performing data analysis. Since the innovative research proposed in the COBRE projects will yield complex data that may require new statistical methods, the DAC will also develop novel statistical methodology for the design and analysis of neuroimaging and behavioral data. Once an analysis approach is developed, the DAC aims to enable the COBRE PLs to obtain the workflow, so that they could reapply the tools to the same type of experiments. The DAC and the BNC work together to coordinate with the Center for Statistical Sciences, the Data Sciences Initiative, and Center for Computation and Visualization at Brown University, to help the PLs achieve the most efficient, reliable, and reproducible analysis of their research data, and to maintain analysis process in a system that ensures continuity of research within the project and lowers the boundary for cross-project transferring, as well as dissemination to the external scientific community. The DAC will extend its support to the large community at Brown University and its affiliated hospitals, by providing training opportunities together with other entities that also promote interdisciplinary research, including the Data Science Initiative, the Advance Clinical and Translational Research and other COBRE centers in Rhode Island.

设计和分析核心（DAC）的使命是为神经科学提供教职员工的支持 原则研究设计，统计建模，推理，机器学习和高性能研究 计算。 DAC与行为和神经影像核（BNC）互补，但与 BNC提供实用的实施服务。 DAC在II阶段中具有以下特定目标： （1）为设计领导者（PLS）提供针对特定项目的教职员工合作 分析; （2）开发用于研究设计的新型统计方法和计算工具箱 全面分析神经影像和行为数据； （3）协调并促进进入 布朗大学中央计算和信息基础设施，并为数据提供补充支持 管理; （4）作为培训和交流计算神经科学和交流的目的 将统计和计算支持扩展到不断增长的神经科学研究人员社区 罗德岛。 DAC由生物统计学和计算机科学系的四名教职员工组成， 两名员工科学家，一个与BNC共享。 DAC将通过匹配教职 通过指导实验设计，确定足够的统计和 计算方法和执行数据分析。自从提出的创新研究 山羊项目将产生可能需要新统计方法的复杂数据，DAC也将开发 用于设计和分析神经影像和行为数据的新型统计方法。一次 开发了分析方法，DAC旨在使毛绒PLS获得工作流程，以便它们 可以将工具重新申请到相同类型的实验中。 DAC和BNC一起工作以协调 与统计科学中心，数据科学计划以及计算中心 布朗大学的可视化，以帮助PLS实现最有效，可靠和可重现的分析 他们的研究数据，并在系统中维护分析过程，以确保在 该项目并降低了跨项目转移的边界，以及向外部传播 科学界。 DAC将向布朗大学及其附属医院的大型社区提供支持，由 与其他也促进跨学科研究的实体提供培训机会， 包括数据科学计划，预先临床和转化研究以及其他毛病 罗德岛的中心。