ポスター発表
- 第1日 5月11日（月） P会場（1008/09）
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1P-04 PDF
ピーク形状に着目した高分解能マススペクトルからのノイズピーク除去方法の検討
Matrix assisted laser desorption/ionization (MALDI) mass spectrometry is a powerful tool for the analysis of synthetic polymers. By using MALDI with a high-resolution time-of-flight mass spectrometer, this technique can be used to identify differences in polymer end groups and their molecular weight distributions. Kendrick mass defect (KMD) analysis of this data simplifies the data interpretation, even for complicated mass spectra, by showing an overview of the differences observed within a sample. However, the wide and distorted peaks are often observed in the low mass region of MALDI mass spectrum. They are exponentially decreased according to increasing mass. In order to see the polymer series clearly in the KMD analysis, it is important to reduce these noise signal automatically. In this presentation, we will report on the noise peak reduction method for high resolution mass spectrum by using the machine learning technique.