Towards Reliable, Reproducible and Standardized MALDI Mass Spectrometry Imaging
Quality assessment, standardization and reproducibility in MALDI MSI - MALDISTAR
The MALDISTAR project aims at improving standardization and reproducibility for MALDI imaging applications. Focusing on pilot scenarios in imaging of peptides and small molecules from FFPE and fresh-frozen tissue, we are investigating and developing methods for quality assessment, data normalization and enhanced data comparability.
01 / QQ Metrics
Develop quantitative quality metrics (QQ Metrics) that allow evaluating whether a given MALDI MSI dataset should be rejected or is of sufficient quality for a given analysis task, or whether multiple datasets show sufficiently similar characteristics in order to be analyzed collectively.
MALDISTAR is kindly funded by the Klaus Tschira Foundation (grant 00.010.2019).
MALDISTAR is hiring!
Looking for a job or PhD position? Join the MALDISTAR team as a data scientist / mathematician / bioinformatician!
See MALDISTAR job postings for further information
Peter Maass, PhD
Lena Hauberg-Lotte, PhD
Denis Abu Sammour, MSc
Carsten Hopf, PhD
Tobias Boskamp, PhD
(Bruker Daltonik GmbH)
Scientific Advisors