国家重点基础研究发展计划(973)(2001CB510209),国家高技术研究发展计划(863)(2002-BA711A11,2004BA711A21),北京市重大科技专项(H03023280590)和国家自然科学基金资助项目(321003).
This work was supported by grants from The National Basic Research Program of China (2001CB510209), Hi-Tech Research and Development Program of China (2002BA711A11,2004BA711A21), Beijing Municipal Science and Technology Project (H030230280590), and The National Natural Science Foundation of China (321003).
挖掘高通量实验数据蕴含的生物学意义是蛋白质组学研究面临的一大挑战 . 基于等级化结构化的词汇表 GO (Gene Ontology) 和相关数据库中的蛋白质功能注释,发展了一种对蛋白质组学研究中得到的表达谱 (Expression profile) 进行功能分析的策略 . 在对蛋白质表达谱进行功能注释的基础上给出蛋白质表达谱中蛋白质功能的分布,同时给出感兴趣功能类别的统计信息 . 这有助于对表达谱蛋白质功能的整体理解和深入的生物信息学分析 . 该策略已经成功应用胎肝蛋白表达谱研究中,用户可以通过访问网址 http://www.hupo.org.cn/GOfact/ 使用或者下载我们的程序 .
Data analysis poses a significant challenge to the large-scale proteomics studies. Based on the structured and controlled vocabularies-Gene Ontology (GO), and the GO annotation from related databases, a strategy composed of several programs and local databases is developed to identify the functional distribution and the significantly enriched functional categories of the proteomic expression profile. It would be helpful for understanding the overall functions of these identified proteins and supply the fundamental information for further bioinformatics exploration. This strategy has been successfully used in the Human Fetal Liver (HFL) proteomic research, which is available online at http://www.hupo.org.cn/GOfact/.
李 栋,荔建琦,欧阳曙光,吴松锋,王 建,徐筱杰,朱云平,贺福初.高通量蛋白质组学研究中一种基于 GO 的蛋白质功能分析策略[J].生物化学与生物物理进展,2005,32(11):1026-1029
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