Detection of peptide ion peaks in mass spectra by using weighted auto-correlation

Kenji Watanabe, Takumi Kobayashi, Katsuyuki Koike, Tetsuya Higuchi, Tohru Natsume, Nobuyuki Otsu

Abstract: In biology, peptide ion detection from mass spectra is important for identifying proteins. Many methods have been proposed for detecting peptide ion peaks, some of which use wavelet transform. In these methods, however, the co-occurrence pattern of peptide ions and those isotopes is not directly considered. In this paper, we propose a novel method for detecting peptide ion peaks from a mass spectrum by using a weighted auto-correlation. The weight functions derived from Maxwell-Boltzmann distribution and the sine function are introduced to the proposed auto correlations to effectively represent the peptide ion co-occurrence patterns. The multi-scaled auto-correlation features extracted with those weight functions are compressed by using principal component analysis. Experiments on raw mass spectra show that the proposed method achieves the favorable performances and is capable of automatically detecting peptide ion peaks.