Concise representation of mass spectrometry images by probabilistic latent semantic analysis

Analytical Chemistry

Volumn 80, Issue 24, 2008, Pages 9649-9658

  Hanselmann, Michael ^a   Kirchner, Marc ^a   Renard, Bernhard Y ^a   Amstalden, Erika R ^b   Glunde, Kristine ^c   Heeren, Ron M A ^b   Hamprecht, Fred A ^a  

^a UNIVERSITY OF HEIDELBERG   (Germany)

^b FOM INSTITUTE AMOLF   (Netherlands)

^c JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AKAIKE INFORMATION CRITERIONS; COMPLEXITY ESTIMATES; CONCISE REPRESENTATIONS; CURRENT APPLICATIONS; EXPLORATORY DATA ANALYSES; IMAGING MASS SPECTROMETRIES; INDEPENDENT COMPONENTS; NUMBER OF COMPONENTS; ORGANIC SAMPLES; PARAFAC; PARALLEL FACTORS ANALYSES; PHYSICAL INTERPRETATIONS; PRINCIPAL COMPONENTS; PROBABILISTIC LATENT SEMANTIC ANALYSES; RECONSTRUCTION ACCURACIES; SPATIAL DISTRIBUTIONS; SPATIAL STRUCTURES; STATISTICAL COMPLEXITIES; TISSUE SAMPLES;

HEMODYNAMICS; HIGH PERFORMANCE LIQUID CHROMATOGRAPHY; IMAGE ENHANCEMENT; IMAGE RETRIEVAL; INFORMATION THEORY; INSULATING MATERIALS; MASS SPECTROMETERS; MASS SPECTROMETRY; MULTIVARIANT ANALYSIS; OPTICAL PROJECTORS; PARALLEL ALGORITHMS; PRINCIPAL COMPONENT ANALYSIS; PROBABILITY; PROBABILITY DISTRIBUTIONS; SECONDARY ION MASS SPECTROMETRY; SEMANTICS; SPECTROMETERS; SPECTROMETRY; SPECTRUM ANALYSIS;

INDEPENDENT COMPONENT ANALYSIS;

ALGORITHMS; BREAST NEOPLASMS; COMPUTER SIMULATION; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MASS SPECTROMETRY; PRINCIPAL COMPONENT ANALYSIS; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 58149113051     PISSN: 00032700     EISSN: None     Source Type: Journal    
DOI: 10.1021/ac801303x     Document Type: Article

References (33)

1. Caprioli, R. M.; Farmer, T. B.; Gile, J. Anal. Chem. 1997, 69, 4751-4760.
2. McDonnell, L. A.; Heeren, R. M. A. Mass Spectrom. Rev. 2006, 26, 606-643.
3. Chaurand, P.; Schwartz, S. A.; Caprioli, R. M. Curr. Opin. Chem. Biology 2002, 6, 676-681.
4. Simpkins, F.; Czechowicz, J. A.; Liotta, L.; Kohn, E. C. Pharmacogenomics 2005, 6, 647-653.
5. Yanagisawa, K.; Shyr, Y.; Xu, B.; Massion, P.; Larsen, P.; White, B.; Roberts, J.; Edgerton, M.; Gonzalez, A.; Nadaf, S. The Lancet 2003, 362, 433-439.
6. Rohner, T. C.; Staab, D.; Stoeckli, M. Mech. Ageing Dev. 2005, 126, 177-185.
7. Belu, A. M.; Davies, M. C.; Newton, J. M.; Patel, N. Anal. Chem. 2000, 72, 5625-5638.
8. Cornett, D. S.; Frappier, S. L.; Caprioli, R. M. Anal. Chem. 2008, 80, 5648-5653.
9. Wu, L.; Lu, X.; Kulp, K. S.; Knize, M. G.; Berman, E. S. F.; Nelson, E. J.; Felton, J. S.; Wu, K. J. J. Int. J. Mass Spectrom. 2007, 2-3, 137-145.
10. Trim, P. J.; Atkinson, S. J.; Princivalle, A. P.; Marshall, P. S.; West, A.; Clench, M. R. Rapid Commun. Mass Spectrom. 2008, 22, 1503-1509.
11. van de Plas, R.; Ojeda, F.; Dewil, M.; van den Bosch, L.; de Moor, B.; Waelkens, E. Proc. Pacific Symp. Biocomput. 2007, 12, 458-469.
12. Ivosev, G.; Burton, L.; Bonner, R. Anal. Chem. 2008, 80, 4933-4944.
13. Mantini, D.; Petrucci, F.; del Boccio, P.; Pieragostino, D.; di Nicola, M.; Lugaresi, A.; Federici, G.; Sacchetta, P.; di Ilio, C.; Urbani, A. Bioinformatics 2008, 24, 63-70.
14. Broersen, A.; van Liere, R.; Heeren, R. M. A. Proceedings of the 5th IASTED International Conference on Visualization, Imaging, and Image Processing, 2005; pp 540-545.
15. Smentkowski, V. S.; Ostrowski, S. G.; Kollmer, F.; Schnieders, A.; Keenan, M. R.; Ohlhausen, J. A.; Kotula, P. G. Surf. Interface Anal. 2008, 40, 1176-1182.
16. Akaike, H. IEEE Trans. Automatic Control 1974, 19, 716-723.
17. Hastie, T.; Tibshirani, R.; Friedman, J. The Elements of Statistical Learning; Springer: New York, 2001.
18. Bro, R. Multi-way Analysis in the Food Industry - Models, Algorithms, and Applications. PhD. thesis, University of Amsterdam, The Netherlands, 1998.
19. Hyvärinen, A.; Oja, E. Neural Networks 2000, 13, 411-430.
20. Gävert, H.; Hurri, J.; Särelä, J.; Hyvärinen, A.http://www.cis.hut.fi/projects/ica/fastica/, 2007.
21. Harshman, R. A. UCLA Work. Pap. Phonetics 1970, 16, 1-84.
22. Carroll, J. D.; Chang, J. J. Psychometrika 1970, 35, 283-819.
23. Kiers, H. A. Psychometrika 1991, 56, 97-212.
24. Cichocki, A.; Zdune, R. Lect. Notes Comput. Sci. 2007, 2007, 793-802.
25. Bro, R.; Andersson, C. A.http://www.models.kvl.dk/source/nwaytoolbox/ index.asp, 2007.
26. Hofmann, T. Proceedings of the 15th Conference on Uncertainty in Artificial Intelligence, 1999.
27. Gaussier, E.; Goutte, C. Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2005; pp 601-602.
28. Benvenuto, F.; La Camera, A.; Theys, C.; Ferrari, A.; Lantri, H.; Bertero, M. Inverse Probl. 2008, 24, 1-20.
29. Stine, R. A. Sociolog. Methods Res. 2004, 33, 230-260.
30. Burnham, K. P.; Anderson, D. R. Model Selection and Multimodel Inference, A Practical-Theoretic Approach, 2nd ed.; Springer: New York, 2002.
31. Renard, B. Y.; Kirchner, M.; Steen, H.; Steen, J. A.; Hamprecht, F. A.; BMC Bioinf. 2008, 9, 355.
32. Hoyer, P. J. Machine Learn. Res. 2004, 5, 1457-1469.
33. Personal communication.