Integrative Neuroinformatics for Neuroanatomy

破译人类基因组使我们能够发现特定基因和疾病之间的联系。它还使我们能够测量大脑中所有基因的表达或使用。大脑是人类已知的最复杂的物体，这种复杂性体现在大脑中基因使用的不同，四分之三的基因在不同的脑区或年龄发生变化。虽然已知许多基因直接影响大脑结构，但许多用于大脑的基因发挥着未知的作用。这项研究试图找到基因使用的模式，以帮助理解人类大脑的其他三个指标。第一个是神经解剖学，我们试图通过结合几个基因使用的大型数据集来寻找大脑不同区域和不同层之间的差异基因。其次，我们将把基因使用信息与磁共振扫描(MRI)产生的灰度图像结合起来。最后，我们通过用特定的标签标记基因组来检查影响基因使用的表观遗传信息。我们将测试基因使用和这些甲基化标签之间的关系是否会随着时间或性别的不同而不同。这项工作旨在增加我们对神经图像、大脑结构和基因使用控制的分子的理解。这些项目将由学生承担，他们将学习如何应用数据科学方法来处理庞大而复杂的数据集。*根据加拿大精神卫生协会的数据，五分之一的加拿大人在一生中会经历精神疾病。减轻这种沉重的负担受到大脑复杂性的限制，这对我们寻找治疗方法的努力构成了挑战。我们的上述工作包括检查多组基因，这对理解复杂的精神疾病至关重要。对于精神分裂症、抑郁症和智力残疾这样的疾病，我们不知道大脑的哪些组成部分受到了干扰。然而，我们确实知道这些疾病与许多基因的变化有关。我们对基因在大脑中作用的研究可能有助于找到与心理健康相关的基因的共同特征。这些线索可以帮助指导治疗。在这方面，我们所有的工具都将是开源的，并在网上免费提供，让其他人看到他们在大脑中感兴趣的基因。

Decoding the human genome has allowed us to discover associations between specific genes and diseases. It has also enabled us to measure expression or usage of all genes in the brain. The brain is the most complex object known to man, this complexity is seen in differences in gene usage in the brain, with three-quarters of genes changing across brain regions or age. While many genes are known to directly affect brain structure, many genes used in the brain play unknown roles. This research seeks to find patterns of gene usage that can help understand three other measures of the human brain. The first is neuroanatomy, we seek to find genes that differ across different regions and layers of the brain by combining several large datasets of gene usage. Second, we will join gene usage information with the grayscale images produced from magnetic resonance scans (MRI). Lastly, we examine epigenetic information that influences gene usage by marking the genome with specific tags. We will test if the relationships between gene usage and these methylation tags are different across time or sex. This work aims to increase our understanding of the molecules underlying neuroimages, brain structure, and control of gene usage. These projects will be undertaken by students that will learn how to apply data science methods to handle the large and complex datasets.******According to the Canadian Mental Health Association, one in five Canadians will experience mental illness in their lifetime. Reducing this high burden is limited by the complexity of the brain, challenging our efforts to find cures. Our above work that involves examining sets of genes is of key importance to understanding complex mental illness. For disorders like schizophrenia, depression, and intellectual disability we do not understand which components of the brain are disrupted. However, we do know that these disorders are associated with changes in many genes. Our work to characterize what genes are doing in the brain may help find common characteristics of mental health associated genes. These clues can help guide therapeutic treatments. In this regard, all of our tools will be open source and freely available online for others to see their genes of interest across the landscape of the brain.