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MET-IDEA: Data Extraction Tool for Mass Spectrometry-Based Metabolomics

机译:MET-IDEA:基于质谱的代谢组学的数据提取工具

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摘要

A current and significant limitation to metabolomics is the large-scale, high-throughput conversion of raw chromatographically coupled mass spectrometry datasets into organized data matrices necessary for further statistical processing and data visualization. This article describes a new data extraction tool, MET-IDEA (Metabolomics Ion-based Data Extraction Algorithm) which surmounts this void. MET-IDEA is compatible with a diversity of chromatographically coupled mass spectrometry systems, generates an output similar to traditional quantification methods, utilizes the sensitivity and selectivity associated with selected ion quantification, and greatly reduces the time and effort necessary to obtain large-scale organized datasets by several orders of magnitude. The functionality of MET-IDEA is illustrated using metabolomics data obtained for elicited cell culture exudates from the model legume, Medicago truncatula. The results indicate that MET-IDEA is capable of rapidly extracting semiquantitative data from raw data files, which allows for more rapid biological insight. MET-IDEA is freely available to academic users upon request.
机译:代谢组学的当前重大限制是将原始色谱耦合的质谱数据集大规模,高通量转换为进一步的统计处理和数据可视化所必需的有组织的数据矩阵。本文介绍了一种新的数据提取工具MET-IDEA(基于Metabolomics离子的数据提取算法),它可以克服这一空白。 MET-IDEA与多种色谱耦合质谱系统兼容,产生类似于传统定量方法的输出,利用与选定离子定量相关的灵敏度和选择性,并大大减少了获得大规模有序数据集所需的时间和精力上升了几个数量级。使用代谢组学数据说明了MET-IDEA的功能,代谢组学数据是从豆科植物苜蓿苜蓿(Medicago truncatula)模型引起的细胞培养液分泌物中获得的。结果表明,MET-IDEA能够从原始数据文件中快速提取半定量数据,从而可以更快地进行生物学洞察。 MET-IDEA可应要求免费提供给学术用户。

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