Garrels James I
Funct Integr Genomics. 2002 Sep;2(4-5):212-37. doi: 10.1007/s10142-002-0061-7. Epub 2002 May 24.
Since the completion of the yeast genome sequence in 1996, three genomic databases, the Saccharomyces Genome Database, the Yeast Proteome Database, and MIPS (produced by the Munich Information Center for Protein Sequences), have organized published knowledge of yeast genes and proteins onto the framework of the genome. Now, post-genomic technologies are producing large-scale datasets of many types, and these pose new challenges for knowledge integration. This review first examines the structure and content of the three genomic databases, and then draws from them and other resources to examine the ways knowledge from the literature, genome, and post-genomic experiments is stored, integrated, and disseminated. To better understand the impact of post-genomic technologies, 20 collections of post-genomic data were analyzed relative to a set of 243 previously uncharacterized genes. The results indicate that post-genomic technologies are providing rich new information for nearly all yeast genes, but data from these experiments is scattered across many Web sites and the results from these experiments are poorly integrated with other forms of yeast knowledge. Goals for the next generation of databases are set forth which could lead to better access to yeast knowledge for yeast researchers and the entire scientific community.
自1996年酵母基因组序列完成以来，三个基因组数据库，即酿酒酵母基因组数据库、酵母蛋白质组数据库和MIPS（由慕尼黑蛋白质序列信息中心制作），已将已发表的酵母基因和蛋白质知识整理到基因组框架上。如今，后基因组技术正在产生多种类型的大规模数据集，这些数据集给知识整合带来了新的挑战。本综述首先考察这三个基因组数据库的结构和内容，然后借鉴这些数据库及其他资源，探讨来自文献、基因组和后基因组实验的知识是如何存储、整合和传播的。为了更好地理解后基因组技术的影响，相对于一组243个以前未表征的基因，分析了20组后基因组数据。结果表明，后基因组技术正在为几乎所有酵母基因提供丰富的新信息，但这些实验的数据分散在许多网站上，且这些实验的结果与酵母知识的其他形式整合得很差。文中提出了下一代数据库的目标，这可能会使酵母研究人员和整个科学界能更好地获取酵母知识。
