Deciphering brain phenotypes from analysis of multiple data types; integrative

这个项目的总体目标是对表型-基因-环境关联进行建模和预测。 使用与神经精神病学表型相关的多种数据类型。虽然全球各地的众多团体 解决更大的问题，即追踪影响复杂性表现的环境和遗传因素 关于人类的特征，这些研究中只有一小部分与神经精神表型有关。致我们的 知识，没有全面的建模方法和对多线程实验的计算审查 证据是存在的。该项目旨在填补这一空白；它是所有建议的建模的焦点 在这里，它汇聚了中心的所有项目和所有专家，就建模问题达成共识 假设和分析，以使数据正常化的方法，以及以评估全球 推论。

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.