Research group Anneli Kruve group
We use modelling and machine learning to understand ionization processes in electrospray (ESI) and developing semi-quantitative non-targeted analysis methodology.
Group description
Quantification is crucial in all branches of analytical chemistry: environmental analysis, metabolomics, and monitoring food contaminants. The method of choice often is mass spectrometry, which guarantees low detection limits and high selectivity. However, targeted analysis is often tedious and limited in their coverage as standards are needed to evaluate the vast differences in ionization efficiencies of different compounds in the electrospray ionization source.
The non-targeted analysis with mass spectrometry has been developed to allow detection of contaminants, metabolites, etc. without the use of standard compounds. Still, the lack of quantitative information remains one of the major bottlenecks in non-targeted metabolomics. We develop novel strategies for non-targeted quantification using conventional LC-MS and machine learning approaches.
We apply these methods to obtain quantitative results in a number of applications from emerging contaminants in water to metabolites in cell cultures.
Group members
Group managers
Anneli Kruve
Associate Professor
Members
Yvonne Kreutzer
PhD student
Ida Rahu
Postdoktor
Anselm Irenäus Gordian Sandberg
PhD student
Henrik Hupatz
Postdoc
Wei-Chieh Wang
PhD Student
Louise Malm
PhD Student
Helen Sepman
PhD student
Amina Souihi
Doktorand
Drew Szabo
Postdoktor
