Current State of HPLC-MS Data Processing and Analysis in Proteomics and Metabolomics
High performance liquid chromatography (HPLC) in tandem with mass spectrometry (MS) is widely used in
chemical and biochemical analysis of the content of measured samples, especially in so-called omics science. Currently,
there are methods for processing and analyzing the measured data sets from proteomics as well as metabolomics. However,
only some of the problems of processing and analyzing tasks have been compensated for, and even in these cases,
they have only been considered independently. Therefore, the current state of data handling is studied. This review describes
the currently available methods and techniques commonly used in HPLC-MS for processing and analysis. All the
main types of processing and most popular methods are mentioned. However, any overview will fail to be exhaustive.
Therefore, some additional literature that goes into further detail is recommended. The review itself reveals some of the
important shortcomings of the current state of the art. A list of relevant subtopics relating to different research focuses is
provided in the conclusion.
Keywords: Feature detection, liquid chromatography, mass spectrometry, time alignment, Correlation optimized warping, Dynamic time warping, Full width at half maximum, High performance liquid chromatography, Internal standard, Multivariate analysis, Total ion current chromatogram, Time of flight
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