Journal
JOURNAL OF CHROMATOGRAPHY A
Volume 1216, Issue 16, Pages 3458-3466Publisher
ELSEVIER
DOI: 10.1016/j.chroma.2008.09.058
Keywords
Two-dimensional chromatography; Liquid chromatography; Chemical identification and classification; Pattern matching; Pattern recognition
Funding
- NCRR NIH HHS [5R44RR20256, R44 RR020256-03] Funding Source: Medline
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Comprehensive two-dimensional liquid chromatography (LC x LC) generates information-rich but complex peak patterns that require automated processing for rapid chemical identification and classification. This paper describes a powerful approach and specific methods for peak pattern matching to identify and classify constituent peaks in data from LC x LC and other multidimensional chemical separations. The approach records a prototypical pattern of peaks with retention times and associated metadata. such as chemical identities and classes, in a template. Then, the template pattern is matched to the detected peaks in subsequent data and the metadata are copied from the template to identify and classify the matched peaks. Smart Templates employ rule-based constraints (e.g., multispectral matching) to increase matching accuracy. Experimental results demonstrate Smart Templates, with the combination of retention-time pattern matching and multispectral constraints, are accurate and robust with respect to changes in peak patterns associated with variable chromatographic conditions. (C) 2008 Elsevier B.V. All rights reserved.
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