Smart Templates for peak pattern matching with comprehensive two-dimensional liquid chromatography

Stephen E. Reichenbach, Peter W. Carr, Dwight R. Stoll, Qingping Tao

Research output: Contribution to journalArticlepeer-review

68 Scopus citations


Comprehensive two-dimensional liquid chromatography (LC× 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× 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.

Original languageEnglish (US)
Pages (from-to)3458-3466
Number of pages9
JournalJournal of Chromatography A
Issue number16
StatePublished - Apr 17 2009
Externally publishedYes


  • Chemical identification and classification
  • Liquid chromatography
  • Pattern matching
  • Pattern recognition
  • Two-dimensional chromatography

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Organic Chemistry


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