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

Prof. Dr. Benjamin Balluff

Imaging Mass Spectrometry

Maastricht University

The Netherlands

Prof. Dr. Ferdinand von Eggeling

MALDI Imaging

University Hospital Jena

Germany

Prof. Dr. Charles Pineau

Inserm Unit 1085

Protim - University of Rennes

France

Prof. Dr. Pierre Chaurand

Imaging Mass Spectrometry Lab

Université de Montreal

Canada

 

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