Probabilistic Segmentation of Mass Spectrometry (MS) Images Helps Select Important Ions and Characterize Confidence in the Resulting Segments-Reference-Cited by-同舟云学术

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

Published:2016-05 Issue:5 Volume:15 Page:1761-1772
ISSN:1535-9476
Container-title:Molecular & Cellular Proteomics
language:en
Short-container-title:Molecular & Cellular Proteomics

Author:

Bemis Kyle D.,Harry April,Eberlin Livia S.,Ferreira Christina R.,van de Ven Stephanie M.,Mallick Parag,Stolowitz Mark,Vitek Olga

Funder

NSF

Canary Foundation

Publisher

Elsevier BV

Subject

Molecular Biology,Biochemistry,Analytical Chemistry

Reference21 articles.

1. MALDI imaging mass spectrometry: Statistical data analysis and current computational challenges;Alexandrov;BMC Bioinformatics,2012

2. Testing for presence of known and unknown molecules in imaging mass spectrometry;Alexandrov;Bioinformatics,2013

3. Spatial segmentation of imaging mass spectrometry data with edge-preserving image denoising and clustering;Alexandrov;J. Proteome Res,2010

4. Efficient spatial segmentation of large imaging mass spectrometry datasets with spatially aware clustering;Alexandrov;Bioinformatics,2011

5. Cardinal: An R package for statistical analysis of mass spectrometry-based imaging experiments;Bemis;Bioinformatics,2015

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