Allen Institute for Brain Science, Seattle, Washington, USA.
Int Rev Neurobiol. 2012;104:159-82. doi: 10.1016/B978-0-12-398323-7.00007-0.
Large-scale databases of the brain are providing content to the neuroscience community through molecular, cellular, functional, and connectomic data. Organization, presentation, and maintenance requirements are substantial given the complexity, diverse modalities, resolution, and scale. In addition to microarrays, magnetic resonance imaging, and RNA sequencing, several in situ hybridization databases have been constructed due to their value in spatially localizing cellular expression. Scalable techniques for processing and presenting these data for maximum utility in viewing and analysis are key for end user value. We describe methods and use cases for the Allen Brain Atlas resources of the adult and developing mouse.
大型脑数据库通过分子、细胞、功能和连接组学数据为神经科学领域提供内容。鉴于其复杂性、多种模态、分辨率和规模,组织、呈现和维护要求非常高。除了微阵列、磁共振成像和 RNA 测序外,由于其在空间定位细胞表达方面的价值,还构建了几个原位杂交数据库。处理和呈现这些数据的可扩展技术对于最大限度地提高在查看和分析中的效用对于最终用户价值至关重要。我们描述了用于处理和呈现这些数据的方法和用例,这些数据来自成年和发育中的小鼠的艾伦大脑图谱资源。