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Overview: This paper from Institute of Electrical and Electronics Engineers present two techniques to improve the computational efficiency of protein discovery from mass spectrometry databases: noise filtering and hierarchical searching. The papers approaches are orthogonal to existing algorithms and are based on the observation that typical mass spectrometry data contains a large amount of noise that can lead to wasteful computation. The first improvement uses standard machine learning techniques with novel feature vectors derived from the mass spectra to identify and filter the noisy spectra.
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