Lee Vivian, Camon Evelyn, Dimmer Emily, Barrell Daniel, Apweiler Rolf
EMBL Outstation-European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.
In Silico Biol. 2005;5(1):5-8.
The number of large-scale experimental datasets generated from high-throughput technologies has grown rapidly. Biological knowledge resources such as the Gene Ontology Annotation (GOA) database, which provides high-quality functional annotation to proteins within the UniProt Knowledgebase, can play an important role in the analysis of such data. The integration of GOA with analytical tools has proved to aid the clustering, annotation and biological interpretation of such large expression datasets. GOA is also useful in the development and validation of automated annotation tools, in particular text-mining systems. The increasing interest in GOA highlights the great potential of this freely available resource to assist both the biological research and bioinformatics communities.
通过高通量技术生成的大规模实验数据集数量迅速增长。诸如基因本体注释（GOA）数据库之类的生物知识资源可为通用蛋白质数据库（UniProt Knowledgebase）中的蛋白质提供高质量的功能注释，在这类数据的分析中可发挥重要作用。事实证明，将GOA与分析工具相结合有助于对此类大型表达数据集进行聚类、注释和生物学解释。GOA在自动化注释工具尤其是文本挖掘系统的开发和验证中也很有用。对GOA日益增长的兴趣凸显了这一免费资源在协助生物研究和生物信息学领域方面的巨大潜力。
