MULTIVARIATE DISTANCE MATRIX REGRESSION OF BRAIN-IMAGING PHENOTYPES AND GENOTYP

脑成像表型和基因型的多变量距离矩阵回归

• 批准号: 7956323
• 负责人: NICHOLAS Joseph SCHORK
• 金额: $ 0.09万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2010-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7956323
• 关键词: Biomedical Research; Brain imaging; Computer Retrieval of Information on Scientific Projects Database; Data; Functional Magnetic Resonance Imaging; Funding; Genetic; Grant; High Performance Computing; Institution; Modality; Phenotype; Research; Research Personnel; Resources; Source; Techniques; United States National Institutes of Health; tool

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Multivariate tools will be necessary for the integration of high-dimensional data from brain-imaging and genetics modalities. We propose using the Multivariate Distance Matrix Regression technique to associate potentially 500,000 SNPs with 70,000 voxels of fMRI brain images. This will take massive computing power.

该副本是利用众多研究子项目之一 由NIH/NCRR资助的中心赠款提供的资源。子弹和 调查员（PI）可能已经从其他NIH来源获得了主要资金， 因此，可以在其他清晰的条目中表示。列出的机构是 对于中心，这不一定是调查员的机构。 多元工具对于从脑成像和遗传学方式中整合高维数据是必需的。我们建议使用多元距离矩阵回归技术将潜在的500,000个SNP与70,000个fMRI脑图像相关联。这将具有巨大的计算能力。