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Cited by 325

The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index.

Advanced MALDI mass spectrometry imaging in pharmaceutical research and drug development

Open access
Schulz, Sandra, Becker, Michael, Groseclose, M. Reid, Schadt, Simone, Hopf, Carsten·2019·Current Opinion in Biotechnology

Abstract

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) has emerged as a key technology for label-free bioanalysis of the spatial distribution of biomolecules, pharmaceuticals and other xenobiotics in tissue sections. Recent advances in instrumentation, sample preparation, multimodal workflows, quantification, analytical standardization and 'big data' processing have led to widespread utilization of MALDI MSI in pharmaceutical research. These developments have led to applications of the technology in drug discovery beyond drug disposition analysis, most notably in pharmacodynamic biomarker research and in toxicology.

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Registry

Crossref · 10.1016/j.copbio.2018.08.003

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Metadata

Authors
Schulz, S., Becker, M., Groseclose, M. R., Schadt, S., & Hopf, C.
Venue
Current Opinion in Biotechnology
Publisher
Elsevier BV
Published
2019-02
Volume
55
Pages
51-59
ISSN
0958-1669 (ISSN-L)
OpenAlex
W2888486111
Cited by
325
References
59
FWCI
2.68
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Advanced MALDI mass spectrometry imaging in pharmaceutical research and drug development. https://app.cochat.ai/papers/10.1016/j.copbio.2018.08.003
The paper
Schulz, S., Becker, M., Groseclose, M. R., Schadt, S., & Hopf, C. (2019). Advanced MALDI mass spectrometry imaging in pharmaceutical research and drug development. Current Opinion in Biotechnology. https://doi.org/10.1016/j.copbio.2018.08.003

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.