Imperial College London
Dr James McKenzie

DrJamesMcKenzie

Faculty of Medicine, Department of Metabolism, Digestion and Reproduction

Research Associate
 
 
 
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Contact

 

j.mckenzie

 
 
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Location

 

E311Burlington DanesHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Oetjen:2015:10.1186/s13742-015-0059-4,
author = {Oetjen, J and Veselkov, K and Watrous, J and McKenzie, JS and Becker, M and Hauberg-Lotte, L and Kobarg, JH and Strittmatter, N and Mroz, AK and Hoffmann, F and Trede, D and Palmer, A and Schiffler, S and Steinhorst, K and Aichler, M and Goldin, R and Guntinas-Lichius, O and von, Eggeling F and Thiele, H and Maedler, K and Walch, A and Maass, P and Dorrestein, PC and Takats, Z and Alexandrov, T},
doi = {10.1186/s13742-015-0059-4},
journal = {GigaScience},
title = {Benchmark datasets for 3D MALDI- and DESI-imaging mass spectrometry},
url = {http://dx.doi.org/10.1186/s13742-015-0059-4},
volume = {4},
year = {2015}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Background: Three-dimensional (3D) imaging mass spectrometry (MS) is an analytical chemistry technique for the3D molecular analysis of a tissue specimen, entire organ, or microbial colonies on an agar plate. 3D-imaging MS hasunique advantages over existing 3D imaging techniques, offers novel perspectives for understanding the spatialorganization of biological processes, and has growing potential to be introduced into routine use in both biologyand medicine. Owing to the sheer quantity of data generated, the visualization, analysis, and interpretation of 3Dimaging MS data remain a significant challenge. Bioinformatics research in this field is hampered by the lack ofpublicly available benchmark datasets needed to evaluate and compare algorithms.Findings: High-quality 3D imaging MS datasets from different biological systems at several labs were acquired,supplied with overview images and scripts demonstrating how to read them, and deposited into MetaboLights,an open repository for metabolomics data. 3D imaging MS data were collected from five samples using two typesof 3D imaging MS. 3D matrix-assisted laser desorption/ionization imaging (MALDI) MS data were collected frommurine pancreas, murine kidney, human oral squamous cell carcinoma, and interacting microbial colonies culturedin Petri dishes. 3D desorption electrospray ionization (DESI) imaging MS data were collected from a human colorectaladenocarcinoma.Conclusions: With the aim to stimulate computational research in the field of computational 3D imaging MS, selectedhigh-quality 3D imaging MS datasets are provided that could be used by algorithm developers as benchmark datasets.
AU  - Oetjen,J
AU  - Veselkov,K
AU  - Watrous,J
AU  - McKenzie,JS
AU  - Becker,M
AU  - Hauberg-Lotte,L
AU  - Kobarg,JH
AU  - Strittmatter,N
AU  - Mroz,AK
AU  - Hoffmann,F
AU  - Trede,D
AU  - Palmer,A
AU  - Schiffler,S
AU  - Steinhorst,K
AU  - Aichler,M
AU  - Goldin,R
AU  - Guntinas-Lichius,O
AU  - von,Eggeling F
AU  - Thiele,H
AU  - Maedler,K
AU  - Walch,A
AU  - Maass,P
AU  - Dorrestein,PC
AU  - Takats,Z
AU  - Alexandrov,T
DO  - 10.1186/s13742-015-0059-4
PY  - 2015///
SN  - 2047-217X
TI  - Benchmark datasets for 3D MALDI- and DESI-imaging mass spectrometry
T2  - GigaScience
UR  - http://dx.doi.org/10.1186/s13742-015-0059-4
UR  - http://hdl.handle.net/10044/1/24603
VL  - 4
ER  -
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