Neural Network Approach for Mass Spectrometry Prediction by Peptide Prototyping

Scherbart A, Timm W, Boecker S, Nattkemper TW (2007)
In: Artificial Neural Networks – ICANN 2007 - 17th International Conference, Porto, Portugal, September 9-13, 2007, Proceedings, Part II. Sá de JM (Ed); Lecture Notes in Computer Science, 4669. Berlin: Springer: 90-99.

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Sá de, Joaquim Marque
Abstract
In todays bioinformatics, Mass spectrometry (MS) is the key technique for the identification of proteins. A prediction of spectrum peak intensities from pre computed molecular features would pave the way to better understanding of spectrometry data and improved spectrum evaluation. We propose a neural network architecture of Local Linear Map (LLM)-type for peptide prototyping and learning locally tuned regression functions for peak intensity prediction in MALDI-TOF mass spectra. We obtain results comparable to those obtained by ν-Support Vector Regression and show how the LLM learning architecture provides a basis for peptide feature profiling and visualisation.
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Scherbart A, Timm W, Boecker S, Nattkemper TW. Neural Network Approach for Mass Spectrometry Prediction by Peptide Prototyping. In: Sá de JM, ed. Artificial Neural Networks – ICANN 2007 - 17th International Conference, Porto, Portugal, September 9-13, 2007, Proceedings, Part II. Lecture Notes in Computer Science. Vol 4669. Berlin: Springer; 2007: 90-99.
Scherbart, A., Timm, W., Boecker, S., & Nattkemper, T. W. (2007). Neural Network Approach for Mass Spectrometry Prediction by Peptide Prototyping. In J. M. Sá de (Ed.), Lecture Notes in Computer Science: Vol. 4669. Artificial Neural Networks – ICANN 2007 - 17th International Conference, Porto, Portugal, September 9-13, 2007, Proceedings, Part II (pp. 90-99). Berlin: Springer.
Scherbart, A., Timm, W., Boecker, S., and Nattkemper, T. W. (2007). “Neural Network Approach for Mass Spectrometry Prediction by Peptide Prototyping” in Artificial Neural Networks – ICANN 2007 - 17th International Conference, Porto, Portugal, September 9-13, 2007, Proceedings, Part II, ed. J. M. Sá de Lecture Notes in Computer Science, vol. 4669, (Berlin: Springer), 90-99.
Scherbart, A., et al., 2007. Neural Network Approach for Mass Spectrometry Prediction by Peptide Prototyping. In J. M. Sá de, ed. Artificial Neural Networks – ICANN 2007 - 17th International Conference, Porto, Portugal, September 9-13, 2007, Proceedings, Part II. Lecture Notes in Computer Science. no.4669 Berlin: Springer, pp. 90-99.
A. Scherbart, et al., “Neural Network Approach for Mass Spectrometry Prediction by Peptide Prototyping”, Artificial Neural Networks – ICANN 2007 - 17th International Conference, Porto, Portugal, September 9-13, 2007, Proceedings, Part II, J.M. Sá de, ed., Lecture Notes in Computer Science, vol. 4669, Berlin: Springer, 2007, pp.90-99.
Scherbart, A., Timm, W., Boecker, S., Nattkemper, T.W.: Neural Network Approach for Mass Spectrometry Prediction by Peptide Prototyping. In: Sá de, J.M. (ed.) Artificial Neural Networks – ICANN 2007 - 17th International Conference, Porto, Portugal, September 9-13, 2007, Proceedings, Part II. Lecture Notes in Computer Science. 4669, p. 90-99. Springer, Berlin (2007).
Scherbart, Alexandra, Timm, Wiebke, Boecker, Sebastian, and Nattkemper, Tim Wilhelm. “Neural Network Approach for Mass Spectrometry Prediction by Peptide Prototyping”. Artificial Neural Networks – ICANN 2007 - 17th International Conference, Porto, Portugal, September 9-13, 2007, Proceedings, Part II. Ed. Joaquim Marque Sá de. Berlin: Springer, 2007.Vol. 4669. Lecture Notes in Computer Science. 90-99.
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