Evaluation of different techniques for data fusion of LC/MS and 1H-NMR
Evaluation of different techniques for data fusion of LC/MS and 1H-NMR
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DOI：
10.1016/j.chemolab.2006.05.002
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发表时间：
2007-01-15
影响因子：
3.9
通讯作者：
Jacobsson, Sven P.
中科院分区：
文献类型：
--
作者：
Forshed, Jenny;Idborg, Helena;Jacobsson, Sven P.
在对高度复杂的样品进行分析(例如代谢指纹分析)时，如果只使用单一的分析技术，数据可能不足以进行分类。因此，使用两种互补技术，例如LUMS和H-1-核磁共振，可能是有利的。使用两种不同技术的另一个可能的优势是能够验证结果(例如，通过验证新陈代谢模式的时间趋势)。在这项工作中，来自大鼠尿液的LC/MS和H-1-核磁共振数据被用来获得代谢指纹图谱。对两个数据集的三种不同数据融合方法进行了比较，并讨论了数据融合的可能性和困难。在比较串联数据、全层次建模和批处理建模时，前两种方法被发现是最成功的。评估了不同类型的区块缩放和可变缩放，并通过交叉验证找到了每种情况的最佳缩放。最终模型的验证是通过外部测试集进行的。(2)(C)2006 Elsevier B.V.保留所有权利。
In the analyses of highly complex samples (for example, metabolic fingerprinting), the data might not suffice for classification when using only a single analytical technique. Hence, the use of two complementary techniques, e.g., LUMS and H-1-NMR, might be advantageous. Another possible advantage from using two different techniques is the ability to verify the results (for instance, by verifying a time trend of a metabolic pattern). In this work, both LC/MS and H-1-NMR data from analysis of rat urine have been used to obtain metabolic fingerprints. A comparison of three different methods for data fusion of the two data sets was performed and the possibilities and difficulties associated with data fusion were discussed. When comparing concatenated data, full hierarchical modeling, and batch modeling, the first two approaches were found to be the most successful. Different types of block scaling and variable scaling were evaluated and the optimal scaling for each case was found by cross validation. Validations of the final models were performed by means of an external test set.(2) (c) 2006 Elsevier B.V. All rights reserved.