Automated extraction of meaningful pathways from quantitative proteomics data.
Automated extraction of meaningful pathways from quantitative proteomics data.
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从定量蛋白质组学数据中自动提取有意义的途径。
DOI：
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
P. Wright
中科院分区：
文献类型：
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作者：
J. Noirel;S. Ow;G. Sanguinetti;A. Jaramillo;P. Wright
生命科学的技术发展导致数据生产的步伐不断加快。系统生物学试图通过建立描述生物组分之间相互作用的复杂模型来阐明这些数据。然而，从这堆数据中提取信息需要使用复杂的计算技术。在这里，我们提出了一种适合将定量蛋白质组学数据整合到代谢支架中的方法，并确定了集体上调或下调的代谢途径。这种工具的可用性是非常可取的，因为提取的信息可以作为深入分析的起点，特别是在合成生物学等领域，需要对数据集进行常规表征。
Technological developments in the life sciences have resulted in an ever-accelerating pace of data production. Systems Biology tries to shed light upon these data by building complex models describing the interactions between biological components. However, extracting information from this morass of data requires the use of sophisticated computational techniques. Here, we propose a method suitable to integrate data drawn from quantitative proteomics into a metabolic scaffold and identify the metabolic pathways which are collectively up-regulated or down-regulated. The availability of such a tool is highly desirable as the extracted information could then be taken as a starting point for in-depth analyses, in particular in fields like Synthetic Biology, where datasets need be characterized routinely.
影响因子：
7
作者：
Förster, J;Famili, I;Nielsen, J
通讯作者：
Nielsen, J