Suppr超能文献

代谢组学可以从基因组学和蛋白质组学中学到什么?

What can metabolomics learn from genomics and proteomics?

机构信息

Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, Japan.

出版信息

Curr Opin Biotechnol. 2009 Dec;20(6):610-5. doi: 10.1016/j.copbio.2009.09.011. Epub 2009 Oct 21.

Abstract

After nearly a decade, metabolomics has begun to acquire some credence in the scientific community although its acceptance cannot be compared with that of its forerunners, genomics and proteomics. The legitimization of metabolomics as a valid scientific entity depends on the size of the research community it influences. By far the most effective medium for inoculation is the web infrastructure: public servers that accommodate experimental data, simple formats and guidelines for their interpretation, and connectivity between data and tools for analysis. When these elements satisfy the condition to initiate a social epidemic, metabolomics will be accepted as a fundamental data-driven science that can unite hitherto independently conducted research disciplines.

摘要

经过近十年的发展,代谢组学在科学界开始获得一定的认可,尽管其接受程度无法与基因组学和蛋白质组学相媲美。代谢组学作为一个有效的科学实体被认可,取决于它所影响的研究群体的规模。迄今为止,最有效的传播媒介是网络基础设施:公共服务器容纳实验数据,简单的格式和解释指南,以及数据和分析工具之间的连接。当这些元素满足引发社会流行的条件时,代谢组学将被接受为一种基本的数据驱动科学,可以将迄今为止独立进行的研究学科联合起来。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验