scholarly journals Potential use of multivariate curve resolution for the analysis of mass spectrometry images

The Analyst ◽  
2015 ◽  
Vol 140 (3) ◽  
pp. 837-846 ◽  
Author(s):  
Joaquim Jaumot ◽  
Romà Tauler
Keyword(s):  
Mass Spectrometry ◽  
Spatial Distribution ◽  
Mass Spectrometry Imaging ◽  
Multivariate Curve Resolution ◽  
Imaging Data ◽  
Compound Identification ◽  
Curve Resolution ◽  
Potential Use

The application of MCR-ALS to mass spectrometry imaging data provides spatial distribution and MS spectra of components, allowing compound identification.

scholarly journals Automated annotation and visualisation of high-resolution spatial proteomic mass spectrometry imaging data using HIT-MAP

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
G. Guo ◽  
M. Papanicolaou ◽  
N. J. Demarais ◽  
Z. Wang ◽  
K. L. Schey ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Spatial Distribution ◽  
High Resolution ◽  
Mass Spectrometry Imaging ◽  
Direct Detection ◽  
High Mass ◽  
Imaging Data ◽  
Distribution Maps ◽  
Automated Annotation ◽  
Peptide Mass

AbstractSpatial proteomics has the potential to significantly advance our understanding of biology, physiology and medicine. Matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) is a powerful tool in the spatial proteomics field, enabling direct detection and registration of protein abundance and distribution across tissues. MALDI-MSI preserves spatial distribution and histology allowing unbiased analysis of complex, heterogeneous tissues. However, MALDI-MSI faces the challenge of simultaneous peptide quantification and identification. To overcome this, we develop and validate HIT-MAP (High-resolution Informatics Toolbox in MALDI-MSI Proteomics), an open-source bioinformatics workflow using peptide mass fingerprint analysis and a dual scoring system to computationally assign peptide and protein annotations to high mass resolution MSI datasets and generate customisable spatial distribution maps. HIT-MAP will be a valuable resource for the spatial proteomics community for analysing newly generated and retrospective datasets, enabling robust peptide and protein annotation and visualisation in a wide array of normal and disease contexts.

scholarly journals Clusterwise Peak Detection and Filtering Based on Spatial Distribution To Efficiently Mine Mass Spectrometry Imaging Data

2019 ◽  
Vol 91 (18) ◽  
pp. 11888-11896 ◽  
Author(s):  
Jonatan O. Eriksson ◽  
Melinda Rezeli ◽  
Max Hefner ◽  
Gyorgy Marko-Varga ◽  
Peter Horvatovich
Keyword(s):  
Mass Spectrometry ◽  
Spatial Distribution ◽  
Mass Spectrometry Imaging ◽  
Peak Detection ◽  
Imaging Data

scholarly journals Unveiling the spatial distribution of aflatoxin B1 and plant defense metabolites in maize using AP‐SMALDI mass spectrometry imaging

2021 ◽  
Author(s):  
Laura Righetti ◽  
Dhaka Ram Bhandari ◽  
Enrico Rolli ◽  
Sara Tortorella ◽  
Renato Bruni ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Spatial Distribution ◽  
Plant Defense ◽  
Aflatoxin B1 ◽  
Mass Spectrometry Imaging

scholarly journals Evaluation of Digital Image Recognition Methods for Mass Spectrometry Imaging Data Analysis

2018 ◽  
Vol 29 (12) ◽  
pp. 2467-2470 ◽  
Author(s):  
Måns Ekelöf ◽  
Kenneth P. Garrard ◽  
Rika Judd ◽  
Elias P. Rosen ◽  
De-Yu Xie ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
Image Recognition ◽  
Digital Image ◽  
Mass Spectrometry Imaging ◽  
Imaging Data

scholarly journals massPix: an R package for annotation and interpretation of mass spectrometry imaging data for lipidomics

Metabolomics ◽  
2017 ◽  
Vol 13 (11) ◽  
Author(s):  
Nicholas J. Bond ◽  
Albert Koulman ◽  
Julian L. Griffin ◽  
Zoe Hall
Keyword(s):  
Mass Spectrometry ◽  
Mass Spectrometry Imaging ◽  
R Package ◽  
Imaging Data
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