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.

这个项目的总体目标是建立模型并进行表型-基因-环境关联预测 使用与神经精神表型相关的多种数据类型。虽然地球仪上的许多团体 解决追踪影响复杂表现的环境和遗传因素的更大问题 在人类中，这些研究中只有一小部分与神经精神表型有关。对我们 知识，没有整体的建模方法和多线程实验的计算审查 证据是存在的这个项目旨在填补这一空白;它是所有建模建议的焦点 在这里，它汇集了中心的所有项目和所有专家，在建模方面达成共识 假设和分析，数据标准化的方法，以及评估全球 推论