Understanding mass spectrometry images: complexity to clarity with machine learning-Reference-Cited by-同舟云学术

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Understanding mass spectrometry images: complexity to clarity with machine learning

Published:2020-09-16 Issue:4 Volume:112 Page:
ISSN:0006-3525
Container-title:Biopolymers
language:en
Short-container-title:Biopolymers

Author:

Gardner Wil¹²³^ORCID,Cutts Suzanne M.²,Phillips Don R.²,Pigram Paul J.¹^ORCID

Affiliation:

1. Centre for Materials and Surface Science and Department of Chemistry and Physics La Trobe University Melbourne Victoria Australia

2. La Trobe Institute for Molecular Sciences La Trobe University Melbourne Victoria Australia

3. CSIRO Manufacturing Clayton Victoria Australia

Funder

Australian National Fabrication Facility

National Breast Cancer Foundation

Publisher

Wiley

Subject

Organic Chemistry,Biomaterials,Biochemistry,General Medicine,Biophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/bip.23400

Reference70 articles.

1. Hyperspectral Visualization of Mass Spectrometry Imaging Data

2. Data-driven identification of prognostic tumor subpopulations using spatially mapped t-SNE of mass spectrometry imaging data

3. Deep learning and 3D-DESI imaging reveal the hidden metabolic heterogeneity of cancer

4. Rapid MALDI mass spectrometry imaging for surgical pathology

5. Unsupervised machine learning using an imaging mass spectrometry dataset automatically reassembles grey and white matter

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