Chromatographic profiling: From samples to information

Chromatography exists for over a hundred years and has become an important part of analytical chemistry. With the development of new instrumentations and columns that can measure more analytes at higher sensitivities simultaneously a new tool has been made possible: chromatographic profiling. Here, samples are measured untargeted and their entire profiles are then correlated to their properties, the chemical process or whatever type of research question needed to be answered. One special type of application of chromatographic profiling is the so-called -omics application such as e.g. metabolomics.
In chromatographic profiling, huge quantities of data are obtained, and hypothetically, a tremendous increase in information can be obtained from profiling studies. Unfortunately, methods that can deal with the data in a timely manner are still lacking. To date, automated data pre-processing and analysis have become one of the major bottlenecks of large-scale sample analyses. In this thesis, we have tried to deal with some of the issues in a practical yet sound way. We have focused on developing new methods that either result in better data (i.e. more robust and reliable), better pre-processing or better analysis of the data, all with the aim to improve the link from samples to information.