Neuroinformatics for genomics and anatomy

帕夫利迪斯实验室专注于在基因和基因调控水平上分析哺乳动物神经系统，以及这与大脑发育、正常大脑功能和病理过程之间的关系。我们还从事基础基因组学研究，这些研究具有超越神经科学的更广泛影响。一个共同的主题是，我们重新分析、整理和整合大量公开可用的数据。在这项提案中，我们的目标是两个具体的研究项目，这两个项目将提供对基因功能和调控的洞察，这对理解生物生物学至关重要。我们提出的第一个具体项目是分析我们在“Gema”中积累的大量经过管理的基因表达数据中的基因活动模式，“Gema”是一个公开可用并不断扩大的经过管理和重新分析的基因表达数据的数据库(Gemma.msl.ubc.ca，目前有近500,000个样本，代表超过12,000项研究和30,000多个独特的实验条件)。为此，我们最近开发并验证了一种名为“GemmaDE”的算法。我们将根据它们的基因表达模式的相似性，创建一个用于实验的条件网络(例如，药物、基因修改、疾病、发育阶段、性别等)。对这一网络的分析将揭示这数千种不同条件中的哪些彼此相似，从而对基因调控的架构产生新的见解。第二个项目将专注于哺乳动物体内细胞类型和组织内以及跨细胞类型和组织之间的基因活性之间的关系，这是我们实验室最近的工作的延伸。我们将检查基因之间(共表达)与已知和推断的介体和基因调控模式的相关性，并将共表达网络相互比较，以阐明每种数据模式具体发现了哪些类型的调控信息。该项目将广泛利用可公开获得的单细胞基因组学数据，并结合GEMA和第三方来源的其他数据。将这些结果与条件网络相结合也将用于提供与条件相关的候选调节器方面的背景。我们的研究将以对其他研究人员直接有用的方式提高我们对基因功能和调控的理解。在神经科学中的应用包括提高对大脑功能、大脑发育的细胞过程以及神经精神疾病的病因学的基本了解。除了大脑，我们的研究将为数百种细胞类型和数千种实验条件下的基因活动模式和调控因素提供广泛适用的洞察。我们的所有数据和资源都通过网站、软件和应用程序编程接口向公众开放。

The Pavlidis lab focuses on the analysis of the mammalian nervous system at the level of genes and gene regulation, and how this relates to brain development, normal brain function, and pathological processes. We also do basic genomics research that has broader impact beyond neuroscience. A common theme is that we reanalyze, curate and integrate large quantities of publicly-available data. In this proposal we are targeting two specific research projects that will provide insight into gene function and regulation, which is of fundamental importance to understanding organismal biology. The first specific project we propose is to analyze patterns of gene activity in a large body of curated gene expression data we have accumulated in "Gemma", a publicly-available and continually expanding database of curated and re-analyzed gene expression data (gemma.msl.ubc.ca, currently nearly 500,000 samples representing over 12,000 studies and over 30,000 unique experimental conditions). We have recently developed and validated an algorithm, "GemmaDE", for this purpose. We will create a network of conditions used in experiments (e.g. drugs, genetic modifications, disease, developmental stages, sex and others) based on the similarity of their gene expression patterns. Analysis of this network will reveal which of these thousands of diverse conditions resemble each other, yielding new insights into the architecture of gene regulation. The second project will focus on the relationship between gene activity within and across cell types and tissues across the mammalian body, extending recent work from our lab. We will examine correlations between genes (coexpression) with respect to known and inferred mediators and patterns of gene regulation, and compare coexpression networks to each other to elucidate what types of regulatory information is specifically uncovered by each data modality. This project will make extensive use of publicly-available single cell genomics data in combination with other data in Gemma and third-party sources. Integrating these results with the condition network will also be used to provide context in terms of candidate regulators related to conditions. Our research will improve our understanding of gene function and regulation, in ways that are directly useful to other researchers. Applications in neuroscience include improving basic understanding of brain function, cellular processes underlying brain development, as well as the etiology of neuropsychiatric diseases. Beyond the brain, our research will provide broadly applicable insight into modes and regulatory factors underlying gene activity in hundreds of cell types and thousands of experimental conditions. All of our data and resources are made available to the public though web sites, software and application programming interfaces.