Abstract

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Oral Sessions

Day 3, May 17（Fri.）　10:30-10:50　Room D (202)

3D-O1-1030　　PDF

A Novel Peptide Ion Peak Picking Method Based on Deep Learning

(¹DBCLS, ²Kyoto Univ., ³Kyoto Univ., ⁴RIKEN AIP, ⁵Hokkaido Univ.)
^oYuki Moriya¹, Tsuyoshi Tabata^2,3, Mio Iwasaki³, Shin Kawano¹, Susumu Goto¹, Yasushi Ishihama², Ichigaku Takigawa^4,5, Akiyasu Yoshizawa²

Both the detection of monoisotopic peak masses and the charge numbers of peptide ions by "peak-picking" in the MS1, and obtaining a peak list of fragment ions from the MS2 are crucial steps for protein identification in the mass spectrometry (MS)-based proteomics. Although the peak mass and the charge of peptide ion dramatically affect identification of peptide in the database search, detection of accurate mass and charge are often difficult because multiple peaks derived from different peptide ions are overlapping in complex on the mass spectrum. In this study, we tried to detect the peak mass and the charge based on deep learning. As the result, we succeeded in detecting correct peaks that were missed by conventional peak-picking methods.