Deciphering brain phenotypes from analysis of multiple data types; integrative

通过分析多种数据类型破译大脑表型；

• 批准号: 8936056
• 负责人: ANDREY RZHETSKY
• 金额: --
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-22 至 2016-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8936056
• 关键词: Affect; Autistic Disorder; Biological; Brain; Clinical; Complex; Computer Simulation; Consensus; Data; Data Set; Disease; Drug Prescriptions; Environment; Genes; Genetic; Genetic Variation; Goals; Human; Instruction; Knowledge; Maps; Mental Depression; Modeling; Molecular; Patients; Pharmacogenomics; Phenotype; Records; Schizophrenia; System; Testing; Time Series Analysis; clinical phenotype; design; drug mechanism; genetic linkage; genetic linkage analysis; holistic approach; mathematical model; neuropsychiatry; text searching; trait

The overall goal of this project is to model and make phenotype-gene-environment association predictions using multiple data types relevant to neuropsychiatric phenotypes. While numerous groups around the globe tackle the bigger problem of tracing environmental and genetic factors affecting manifestation of complex traits in humans, only a small fraction of these studies is relevant to neuropsychiatric phenotypes. To our knowledge, no holistic approach of modeling and computational scrutiny of multiple threads of experimental evidence exists. This project is designed to fill this gap; it is the focal point of all the modeling proposed here—it brings together all projects and all experts of the Center, to create a consensus on modeling assumptions and analytics, in approaches to normalize data, and in ways to evaluate results of the global inference.

该项目的总体目标是建模并制作表型 - 环境协会的预测 使用与神经精神病表型相关的多种数据类型。而全球许多团体 解决追踪环境和遗传因素影响复杂表现的更大问题 在人类中的特征，只有一小部分研究与神经精神型表型有关。向我们 知识，没有对实验的多个线程进行建模和计算审查的整体方法 存在证据。该项目旨在填补这一空白；这是所有建模建议的焦点 在这里 - 它汇集了所有项目和中心的所有专家，以建立建模共识 假设和分析，以标准化数据的方法以及评估全局结果的方式 推理。