Improved Mass Spectrometry Peak Intensity Prediction by Adaptive Feature Weighting

Scherbart A, Timm W, Böcker S, Nattkemper TW (2008)
In: International Conference on Neural Information Processing. Auckland, New Zealand.

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Konferenzbeitrag | Veröffentlicht | Englisch
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Abstract / Bemerkung
Mass spectrometry (MS) is a key technique for the analysis and identification of proteins. A prediction of spectrum peak intensities from pre computed molecular features would pave the way to a better understanding of spectrometry data and improved spectrum evaluation. The goal is to model the relationship between peptides and peptide peak heights in MALDI-TOF mass spectra, only using the peptide’s sequence information and the chemical properties. To cope with this high dimensional data, we propose a regression based combination of feature weightings and a linear predictor to focus on relevant features. This offers simpler models, scalability, and better generalization. We show that the overall performance utilizing the estimation of feature relevance and re-training compared to using the entire feature space can be improved.
Erscheinungsjahr
Titel des Konferenzbandes
International Conference on Neural Information Processing
Konferenz
ICONIP 2008
Konferenzort
Auckland, New Zealand
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Scherbart A, Timm W, Böcker S, Nattkemper TW. Improved Mass Spectrometry Peak Intensity Prediction by Adaptive Feature Weighting. In: International Conference on Neural Information Processing. Auckland, New Zealand; 2008.
Scherbart, A., Timm, W., Böcker, S., & Nattkemper, T. W. (2008). Improved Mass Spectrometry Peak Intensity Prediction by Adaptive Feature Weighting. International Conference on Neural Information Processing. doi:10.1007/978-3-642-02490-0_63
Scherbart, A., Timm, W., Böcker, S., and Nattkemper, T. W. (2008). “Improved Mass Spectrometry Peak Intensity Prediction by Adaptive Feature Weighting” in International Conference on Neural Information Processing (Auckland, New Zealand).
Scherbart, A., et al., 2008. Improved Mass Spectrometry Peak Intensity Prediction by Adaptive Feature Weighting. In International Conference on Neural Information Processing. Auckland, New Zealand.
A. Scherbart, et al., “Improved Mass Spectrometry Peak Intensity Prediction by Adaptive Feature Weighting”, International Conference on Neural Information Processing, Auckland, New Zealand: 2008.
Scherbart, A., Timm, W., Böcker, S., Nattkemper, T.W.: Improved Mass Spectrometry Peak Intensity Prediction by Adaptive Feature Weighting. International Conference on Neural Information Processing. Auckland, New Zealand (2008).
Scherbart, Alexandra, Timm, Wiebke, Böcker, Sebastian, and Nattkemper, Tim Wilhelm. “Improved Mass Spectrometry Peak Intensity Prediction by Adaptive Feature Weighting”. International Conference on Neural Information Processing. Auckland, New Zealand, 2008.

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