Integrative Neuroinformatics for Neuroanatomy

解码人类基因组使我们能够发现特定基因与疾病之间的联系。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基因使用的差异上，四分之三的基因在大脑区域或年龄上发生变化。虽然已知许多基因直接影响大脑结构，但大脑中使用的许多基因发挥的作用未知。这项研究试图找到基因使用的模式，可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大型基因使用数据集来找到大脑不同区域和不同层次的基因。其次，我们将基因使用信息与磁共振扫描（MRI）产生的灰度图像相结合。最后，我们检查表观遗传信息，影响基因的使用标记的基因组与特定的标签。我们将测试基因使用和这些甲基化标签之间的关系是否随时间或性别而不同。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大型复杂的数据集。

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.