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Siy PW, Moffitt RA, Parry RM, et al. Matrix Factorization Techniques for Analysis of Imaging Mass Spectrometry Data. Proc IEEE Int Symp Bioinformatics Bioeng. 2008;2008doi: 10.1109/BIBE.2008.4696797.
Siy, P. W., Moffitt, R. A., Parry, R. M., Chen, Y., Liu, Y., Sullards, M. C., Merrill, A. H., & Wang, M. D. (2008). Matrix Factorization Techniques for Analysis of Imaging Mass Spectrometry Data. Proceedings. IEEE International Symposium on Bioinformatics and Bioengineering, 2008. https://doi.org/10.1109/BIBE.2008.4696797
Siy, Peter W, et al. "Matrix Factorization Techniques for Analysis of Imaging Mass Spectrometry Data." Proceedings. IEEE International Symposium on Bioinformatics and Bioengineering vol. 2008 (2008). doi: https://doi.org/10.1109/BIBE.2008.4696797
Siy PW, Moffitt RA, Parry RM, Chen Y, Liu Y, Sullards MC, Merrill AH, Wang MD. Matrix Factorization Techniques for Analysis of Imaging Mass Spectrometry Data. Proc IEEE Int Symp Bioinformatics Bioeng. 2008 Oct;2008. doi: 10.1109/BIBE.2008.4696797. Epub 2008 Dec 08. PMID: 28393151; PMCID: PMC5382992.
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Proc IEEE Int Symp Bioinformatics Bioeng. 2008 Oct;2008. doi: 10.1109/BIBE.2008.4696797. Epub 2008 Dec 08.

Matrix Factorization Techniques for Analysis of Imaging Mass Spectrometry Data.

Proceedings. IEEE International Symposium on Bioinformatics and Bioengineering

Peter W Siy, Richard A Moffitt, R Mitchell Parry, Yanfeng Chen, Ying Liu, M Cameron Sullards, Alfred H Merrill, May D Wang

Affiliations

  1. School of Electrical and Computer Engineering, Georgia Tech, Atlanta, GA 30332 USA ( [email protected] ).
  2. Department of Biomedical Engineering, Georgia Tech and Emory University, Atlanta, GA USA ( [email protected] ).
  3. Department of Biomedical Engineering, Georgia Tech and Emory University, Atlanta, GA USA ( [email protected] ).
  4. School of Chemistry & Biochemistry, Georgia Tech, Atlanta, GA USA.
  5. School of Biology, Georgia Tech, Atlanta, GA USA.
  6. Schools of Biology and Chemistry & Biochemistry, Georgia Tech, Atlanta, GA USA.
  7. Schools of Biology and Chemistry & Biochemistry, and the Petit Institute for Bioengineering and Biosciences, Georgia Tech, Atlanta, GA USA.
  8. Department Biomedical Engineering, Georgia Tech and Emory University, the School of Electrical and Computer Engineering, and the Petit Institute for Bioengineering and Biosciences, Georgia Tech, Atlanta, GA USA (phone: 404-385-2954; fax: 404-385-4243; [email protected] ).

PMID: 28393151 PMCID: PMC5382992 DOI: 10.1109/BIBE.2008.4696797

Abstract

Imaging mass spectrometry is a method for understanding the molecular distribution in a two-dimensional sample. This method is effective for a wide range of molecules, but generates a large amount of data. It is difficult to extract important information from these large datasets manually and automated methods for discovering important spatial and spectral features are needed. Independent component analysis and non-negative matrix factorization are explained and explored as tools for identifying underlying factors in the data. These techniques are compared and contrasted with principle component analysis, the more standard analysis tool. Independent component analysis and non-negative matrix factorization are found to be more effective analysis methods. A mouse cerebellum dataset is used for testing.

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Publication Types

Grant support