Wan Xiang, Pavlidis Paul
Department of Psychiatry, UBC Bioinformatics Centre, University of British Columbia, 177 Michael Smith Laboratories 2185 East Mall, Vancouver, BC V6T1Z4, Canada.
Neuroinformatics. 2007 Fall;5(3):161-75. doi: 10.1007/s12021-007-0012-5.
As public availability of gene expression profiling data increases, it is natural to ask how these data can be used by neuroscientists. Here we review the public availability of high-throughput expression data in neuroscience and how it has been reused, and tools that have been developed to facilitate reuse. There is increasing interest in making expression data reuse a routine part of the neuroscience tool-kit, but there are a number of challenges. Data must become more readily available in public databases; efforts to encourage investigators to make data available are important, as is education on the benefits of public data release. Once released, data must be better-annotated. Techniques and tools for data reuse are also in need of improvement. Integration of expression profiling data with neuroscience-specific resources such as anatomical atlases will further increase the value of expression data.
随着基因表达谱数据的公开可得性不断增加,自然而然会有人问神经科学家如何利用这些数据。在此,我们回顾神经科学领域高通量表达数据的公开可得性、其被重复利用的方式,以及为促进重复利用而开发的工具。将表达数据重复利用作为神经科学工具包的常规组成部分的兴趣与日俱增,但仍存在一些挑战。数据必须在公共数据库中更易于获取;鼓励研究人员公开数据的努力很重要,对公开数据发布的益处进行教育也同样重要。一旦数据发布,就必须进行更好的注释。数据重复利用的技术和工具也需要改进。将表达谱数据与解剖图谱等神经科学特定资源整合,将进一步提升表达数据的价值。