Literature DB >> 23873892

Testing for presence of known and unknown molecules in imaging mass spectrometry.

Theodore Alexandrov1, Andreas Bartels.   

Abstract

MOTIVATION: Imaging mass spectrometry has emerged in the past decade as a label-free, spatially resolved and multi-purpose bioanalytical technique for direct analysis of biological samples. However, solving two everyday data analysis problems still requires expert judgment: (i) the detection of unknown molecules and (ii) the testing for presence of known molecules.
RESULTS: We developed a measure of spatial chaos of a molecular image corresponding to a mass-to-charge value, which is a proxy for the molecular presence, and developed methods solving considered problems. The statistical evaluation was performed on a dataset from a rat brain section with test sets of molecular images selected by an expert. The measure of spatial chaos has shown high agreement with expert judges. The method for detection of unknown molecules allowed us to find structured molecular images corresponding to spectral peaks of any low intensity. The test for presence applied to a list of endogenous peptides ranked them according to the proposed measure of their presence in the sample. AVAILABILITY: The source code and test sets of mass-to-charge images are available at http://www.math.uni-bremen.de/∼theodore. SUPPLEMENTARY INFORMATION: Supplementary materials are available at Bioinformatics online. CONTACT: theodore@uni-bremen.de.

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Year:  2013        PMID: 23873892     DOI: 10.1093/bioinformatics/btt388

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  11 in total

1.  FDR-controlled metabolite annotation for high-resolution imaging mass spectrometry.

Authors:  Andrew Palmer; Prasad Phapale; Ilya Chernyavsky; Regis Lavigne; Dominik Fay; Artem Tarasov; Vitaly Kovalev; Jens Fuchser; Sergey Nikolenko; Charles Pineau; Michael Becker; Theodore Alexandrov
Journal:  Nat Methods       Date:  2016-11-14       Impact factor: 28.547

2.  Automated Morphological and Morphometric Analysis of Mass Spectrometry Imaging Data: Application to Biomarker Discovery.

Authors:  Gaël Picard de Muller; Rima Ait-Belkacem; David Bonnel; Rémi Longuespée; Jonathan Stauber
Journal:  J Am Soc Mass Spectrom       Date:  2017-09-14       Impact factor: 3.109

3.  Spatial Metabolomics and Imaging Mass Spectrometry in the Age of Artificial Intelligence.

Authors:  Theodore Alexandrov
Journal:  Annu Rev Biomed Data Sci       Date:  2020-04-13

Review 4.  MALDI-MSI Towards Multimodal Imaging: Challenges and Perspectives.

Authors:  Michael Tuck; Florent Grélard; Landry Blanc; Nicolas Desbenoit
Journal:  Front Chem       Date:  2022-05-09       Impact factor: 5.545

5.  Using collective expert judgements to evaluate quality measures of mass spectrometry images.

Authors:  Andrew Palmer; Ekaterina Ovchinnikova; Mikael Thuné; Régis Lavigne; Blandine Guével; Andrey Dyatlov; Olga Vitek; Charles Pineau; Mats Borén; Theodore Alexandrov
Journal:  Bioinformatics       Date:  2015-06-15       Impact factor: 6.937

6.  BASIS: High-performance bioinformatics platform for processing of large-scale mass spectrometry imaging data in chemically augmented histology.

Authors:  Kirill Veselkov; Jonathan Sleeman; Emmanuelle Claude; Johannes P C Vissers; Dieter Galea; Anna Mroz; Ivan Laponogov; Mark Towers; Robert Tonge; Reza Mirnezami; Zoltan Takats; Jeremy K Nicholson; James I Langridge
Journal:  Sci Rep       Date:  2018-03-06       Impact factor: 4.379

7.  SPUTNIK: an R package for filtering of spatially related peaks in mass spectrometry imaging data.

Authors:  Paolo Inglese; Gonçalo Correia; Zoltan Takats; Jeremy K Nicholson; Robert C Glen
Journal:  Bioinformatics       Date:  2019-01-01       Impact factor: 6.937

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

Authors:  Jonatan O Eriksson; Melinda Rezeli; Max Hefner; Gyorgy Marko-Varga; Peter Horvatovich
Journal:  Anal Chem       Date:  2019-08-23       Impact factor: 6.986

9.  Esmraldi: efficient methods for the fusion of mass spectrometry and magnetic resonance images.

Authors:  Florent Grélard; David Legland; Mathieu Fanuel; Bastien Arnaud; Loïc Foucat; Hélène Rogniaux
Journal:  BMC Bioinformatics       Date:  2021-02-08       Impact factor: 3.169

10.  Probabilistic Segmentation of Mass Spectrometry (MS) Images Helps Select Important Ions and Characterize Confidence in the Resulting Segments.

Authors:  Kyle D Bemis; April Harry; Livia S Eberlin; Christina R Ferreira; Stephanie M van de Ven; Parag Mallick; Mark Stolowitz; Olga Vitek
Journal:  Mol Cell Proteomics       Date:  2016-01-21       Impact factor: 5.911

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